diff --git a/docs/about.md b/docs/about.md
new file mode 100644
index 0000000..bd79c47
--- /dev/null
+++ b/docs/about.md
@@ -0,0 +1,80 @@
+# About the `xcube-resampling` project
+
+## Changelog
+
+You can find the complete `xcube-resampling` changelog 
+[here](https://github.com/xcube-dev/xcube-resampling/blob/main/CHANGES.md). 
+
+## Reporting
+
+If you have suggestions, ideas, feature requests, or if you have identified
+a malfunction or error, then please 
+[post an issue](https://github.com/xcube-dev/xcube-resampling/issues). 
+
+## Contributions
+
+The `xcube-resampling` project welcomes contributions of any form
+as long as you respect our 
+[code of conduct](https://github.com/xcube-dev/xcube-resampling/blob/main/CODE_OF_CONDUCT.md)
+and follow our 
+[contribution guide](https://github.com/xcube-dev/xcube-resampling/blob/main/CONTRIBUTING.md).
+
+If you'd like to submit code or documentation changes, we ask you to provide a 
+pull request (PR) 
+[here](https://github.com/xcube-dev/xcube-resampling/pulls). 
+For code and configuration changes, your PR must be linked to a 
+corresponding issue. 
+
+## Development
+
+To install the `xcube-resampling` development environment into an existing Python 
+environment, do
+
+```bash
+pip install .[dev,doc]
+```
+
+or create a new environment using `conda` or `mamba`
+
+```bash
+mamba env create 
+```
+
+### Testing and Coverage
+
+`xcube-resampling` uses [pytest](https://docs.pytest.org/) for unit-level testing 
+and code coverage analysis.
+
+```bash
+pytest tests/ --cov=xcube_resampling --cov-report html
+```
+
+### Code Style
+
+The `xcube-resampling` source code is formatted and quality-controlled 
+using [ruff](https://docs.astral.sh/ruff/):
+
+```bash
+ruff format
+ruff check
+```
+
+### Documentation
+
+The `xcube-resampling` documentation is built using the 
+[mkdocs](https://www.mkdocs.org/) tool.
+
+With repository root as current working directory:
+
+```bash
+pip install .[doc]
+
+mkdocs build
+mkdocs serve
+mkdocs gh-deploy
+```
+
+## License
+
+`xcube-resampling` is open source made available under the terms and conditions of the 
+[MIT license](https://opensource.org/license/mit).
diff --git a/docs/api.md b/docs/api.md
new file mode 100644
index 0000000..7e2c201
--- /dev/null
+++ b/docs/api.md
@@ -0,0 +1,8 @@
+
+::: xcube_resampling.resample_in_space
+::: xcube_resampling.affine_transform_dataset
+::: xcube_resampling.reproject_dataset
+::: xcube_resampling.rectify_dataset
+::: xcube_resampling.utils
+::: xcube_resampling.gridmapping.GridMapping
+::: xcube_resampling.constants
diff --git a/docs/examples/affine.ipynb b/docs/examples/affine.ipynb
new file mode 100644
index 0000000..a30d03a
--- /dev/null
+++ b/docs/examples/affine.ipynb
@@ -0,0 +1,783 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import numpy as np\n",
+    "from xcube_resampling.affine import affine_transform_dataset\n",
+    "from xcube_resampling.gridmapping import GridMapping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def imshow(var):\n",
+    "    var.plot.imshow(vmin=0, vmax=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 496B\n",
+       "Dimensions:  (lon: 8, lat: 6)\n",
+       "Coordinates:\n",
+       "  * lon      (lon) float64 64B 50.05 50.15 50.25 50.35 50.45 50.55 50.65 50.75\n",
+       "  * lat      (lat) float64 48B 10.55 10.45 10.35 10.25 10.15 10.05\n",
+       "Data variables:\n",
+       "    refl     (lat, lon) float64 384B 0.0 1.0 0.0 2.0 0.0 ... 0.0 2.0 0.0 3.0 0.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1d7202cd-1423-4fc0-a4b8-42a670a9cc8d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1d7202cd-1423-4fc0-a4b8-42a670a9cc8d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 8</li><li><span class='xr-has-index'>lat</span>: 6</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3471fad0-02ac-4383-8b5c-bfdac4aef7ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3471fad0-02ac-4383-8b5c-bfdac4aef7ef' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>50.05 50.15 50.25 ... 50.65 50.75</div><input id='attrs-bab91cd8-e0b3-40a9-98ec-6e74cdd2a715' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bab91cd8-e0b3-40a9-98ec-6e74cdd2a715' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37969ff8-7b9f-47c3-bea2-7c8941e2d366' class='xr-var-data-in' type='checkbox'><label for='data-37969ff8-7b9f-47c3-bea2-7c8941e2d366' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([50.05, 50.15, 50.25, 50.35, 50.45, 50.55, 50.65, 50.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.55 10.45 10.35 10.25 10.15 10.05</div><input id='attrs-8ab8ab20-181f-42c0-baa5-bfc68383a1a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ab8ab20-181f-42c0-baa5-bfc68383a1a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e461b6d-e120-4e39-9359-a29aaef80cc7' class='xr-var-data-in' type='checkbox'><label for='data-1e461b6d-e120-4e39-9359-a29aaef80cc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([10.55, 10.45, 10.35, 10.25, 10.15, 10.05])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea9d7da7-c5fd-41a3-a3fd-47705686e719' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ea9d7da7-c5fd-41a3-a3fd-47705686e719' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>refl</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 0.0 2.0 ... 2.0 0.0 3.0 0.0</div><input id='attrs-43648c33-b2d9-4c58-bf64-ffb8c8ed2dad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43648c33-b2d9-4c58-bf64-ffb8c8ed2dad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cd9fabe-cf8a-4e0a-a2aa-71d4e1d2d392' class='xr-var-data-in' type='checkbox'><label for='data-3cd9fabe-cf8a-4e0a-a2aa-71d4e1d2d392' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0., 1., 0., 2., 0., 3., 0., 4.],\n",
+       "       [2., 0., 3., 0., 4., 0., 1., 0.],\n",
+       "       [0., 4., 0., 1., 0., 2., 0., 3.],\n",
+       "       [1., 0., 2., 0., 3., 0., 4., 0.],\n",
+       "       [0., 3., 0., 4., 0., 1., 0., 2.],\n",
+       "       [4., 0., 1., 0., 2., 0., 3., 0.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dc2e074c-bd95-48d5-bac9-cae0efb53c79' class='xr-section-summary-in' type='checkbox'  ><label for='section-dc2e074c-bd95-48d5-bac9-cae0efb53c79' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c65edc61-a907-448e-b6b7-d9b96c89f790' class='xr-index-data-in' type='checkbox'/><label for='index-c65edc61-a907-448e-b6b7-d9b96c89f790' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             50.05,              50.15,              50.25,\n",
+       "       50.349999999999994, 50.449999999999996,              50.55,\n",
+       "                    50.65,              50.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1c5182c7-a87e-4aea-b852-8f44f273a79f' class='xr-index-data-in' type='checkbox'/><label for='index-1c5182c7-a87e-4aea-b852-8f44f273a79f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([10.549999999999999,              10.45,              10.35,\n",
+       "       10.249999999999998, 10.149999999999999, 10.049999999999999],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9a0b4c5c-108e-450e-bb2f-086bae0cd43f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9a0b4c5c-108e-450e-bb2f-086bae0cd43f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 496B\n",
+       "Dimensions:  (lon: 8, lat: 6)\n",
+       "Coordinates:\n",
+       "  * lon      (lon) float64 64B 50.05 50.15 50.25 50.35 50.45 50.55 50.65 50.75\n",
+       "  * lat      (lat) float64 48B 10.55 10.45 10.35 10.25 10.15 10.05\n",
+       "Data variables:\n",
+       "    refl     (lat, lon) float64 384B 0.0 1.0 0.0 2.0 0.0 ... 0.0 2.0 0.0 3.0 0.0"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "res = 0.1\n",
+    "source_ds = xr.Dataset(\n",
+    "    data_vars=dict(\n",
+    "        refl=xr.DataArray(\n",
+    "            np.array(\n",
+    "                [\n",
+    "                    [0, 1, 0, 2, 0, 3, 0, 4],\n",
+    "                    [2, 0, 3, 0, 4, 0, 1, 0],\n",
+    "                    [0, 4, 0, 1, 0, 2, 0, 3],\n",
+    "                    [1, 0, 2, 0, 3, 0, 4, 0],\n",
+    "                    [0, 3, 0, 4, 0, 1, 0, 2],\n",
+    "                    [4, 0, 1, 0, 2, 0, 3, 0],\n",
+    "                ],\n",
+    "                dtype=np.float64,\n",
+    "            ),\n",
+    "            dims=(\"lat\", \"lon\"),\n",
+    "        )\n",
+    "    ),\n",
+    "    coords=dict(\n",
+    "        lon=xr.DataArray(50.0 + res * np.arange(0, 8) + 0.5 * res, dims=\"lon\"),\n",
+    "        lat=xr.DataArray(10.6 - res * np.arange(0, 6) - 0.5 * res, dims=\"lat\"),\n",
+    "    ),\n",
+    ")\n",
+    "source_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "imshow(source_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((50, 10, 50.8, 10.6), (0.1, 0.1))"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "source_gm = GridMapping.from_dataset(source_ds)\n",
+    "source_gm.xy_bbox, source_gm.xy_res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((3, 3), (50, 10), 0.1, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((3, 3), (50.05, 10.05), 0.1, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=\"bilinear\")\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((8, 6), (50.05, 10.05), 0.1, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=dict(refl= 1))\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((8, 6), (50.2, 10.1), 0.1, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=dict(refl=\"bilinear\"))\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((8, 6), (49.8, 9.9), 0.1, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((8, 6), (50, 10), 0.2, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((8, 6), (49.8, 9.8), 0.2, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)\n",
+    "imshow(target_ds.refl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target_gm = GridMapping.regular((16, 12), (50, 10), 0.05, source_gm.crs)\n",
+    "# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform\n",
+    "target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)\n",
+    "imshow(target_ds.refl)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/examples/coords.ipynb b/docs/examples/coords.ipynb
new file mode 100644
index 0000000..1dae120
--- /dev/null
+++ b/docs/examples/coords.ipynb
@@ -0,0 +1,1591 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import dask.array as da\n",
+    "import numpy as np\n",
+    "import pyproj as pp\n",
+    "import xarray as xr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 72MB\n",
+       "Dimensions:        (y: 1890, x: 1189)\n",
+       "Coordinates:\n",
+       "    lat            (y, x) float64 18MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    lon            (y, x) float64 18MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: y, x\n",
+       "Data variables:\n",
+       "    quality_flags  (y, x) uint32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_3         (y, x) float32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_6         (y, x) float32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_8         (y, x) float32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9d97c6b2-969f-4ad5-b3b6-26921f3b0af9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9d97c6b2-969f-4ad5-b3b6-26921f3b0af9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 1890</li><li><span>x</span>: 1189</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6dc015e2-4abe-42af-b979-873b2de0b39a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6dc015e2-4abe-42af-b979-873b2de0b39a' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-deddca9e-bf07-482d-ab99-f08cb1e2342c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-deddca9e-bf07-482d-ab99-f08cb1e2342c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d71f1250-32d5-48e8-b9a9-e34f1f53b6fa' class='xr-var-data-in' type='checkbox'><label for='data-d71f1250-32d5-48e8-b9a9-e34f1f53b6fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 17.14 MiB </td>\n",
+       "                        <td> 2.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-d96693ec-542c-4e7d-a4a9-c2797ff03b5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d96693ec-542c-4e7d-a4a9-c2797ff03b5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e1c7824-f0a8-49f5-aa27-d4cfaae78e67' class='xr-var-data-in' type='checkbox'><label for='data-4e1c7824-f0a8-49f5-aa27-d4cfaae78e67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 17.14 MiB </td>\n",
+       "                        <td> 2.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-71e5c3c7-6911-4566-88c1-6adcb98ff152' class='xr-section-summary-in' type='checkbox'  checked><label for='section-71e5c3c7-6911-4566-88c1-6adcb98ff152' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>quality_flags</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-6e582c1e-8520-4a49-85b2-63c1d24727b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e582c1e-8520-4a49-85b2-63c1d24727b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef89196d-1f87-4884-b181-ef2a3527615d' class='xr-var-data-in' type='checkbox'><label for='data-ef89196d-1f87-4884-b181-ef2a3527615d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_coding_name :</span></dt><dd>quality_flags</dd><dt><span>flag_descriptions :</span></dt><dd></dd><dt><span>flag_masks :</span></dt><dd>[-2147483648, 1073741824, 536870912, 268435456, 134217728, 67108864, 33554432, 16777216, 8388608, 4194304, 2097152, 1048576, 524288, 262144, 131072, 65536, 32768, 16384, 8192, 4096, 2048, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1]</dd><dt><span>flag_meanings :</span></dt><dd>land coastline fresh_inland_water tidal_region bright straylight_risk invalid cosmetic duplicated sun_glint_risk dubious saturated_Oa01 saturated_Oa02 saturated_Oa03 saturated_Oa04 saturated_Oa05 saturated_Oa06 saturated_Oa07 saturated_Oa08 saturated_Oa09 saturated_Oa10 saturated_Oa11 saturated_Oa12 saturated_Oa13 saturated_Oa14 saturated_Oa15 saturated_Oa16 saturated_Oa17 saturated_Oa18 saturated_Oa19 saturated_Oa20 saturated_Oa21</dd><dt><span>long_name :</span></dt><dd>Classification and quality flags</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_3</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-1e2330d7-255c-4fb5-a607-0b30307ae071' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e2330d7-255c-4fb5-a607-0b30307ae071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2152fc0c-c484-45d6-8373-712029aede62' class='xr-var-data-in' type='checkbox'><label for='data-2152fc0c-c484-45d6-8373-712029aede62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>2.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>442.5</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_6</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-034898b4-a379-4180-9e4b-4dc873db74d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-034898b4-a379-4180-9e4b-4dc873db74d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec125ddd-5246-499d-b1e9-79b56f641602' class='xr-var-data-in' type='checkbox'><label for='data-ec125ddd-5246-499d-b1e9-79b56f641602' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>5.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>560.0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_8</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-a883ef5f-62e6-45ef-9987-e49b7ea06da2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a883ef5f-62e6-45ef-9987-e49b7ea06da2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e664eba8-20d0-4aec-919d-646c5041023b' class='xr-var-data-in' type='checkbox'><label for='data-e664eba8-20d0-4aec-919d-646c5041023b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>7.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>665.0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-10d64c3c-c0f8-4d57-8c3a-1814c98ddd2b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-10d64c3c-c0f8-4d57-8c3a-1814c98ddd2b' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-2e4d819d-ead3-46d1-84db-e7355c379e2e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2e4d819d-ead3-46d1-84db-e7355c379e2e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>product_type :</span></dt><dd>C2RCC_OLCI</dd><dt><span>start_date :</span></dt><dd>04-JUL-2018 09:21:55.677316</dd><dt><span>stop_date :</span></dt><dd>04-JUL-2018 09:23:18.811790</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 72MB\n",
+       "Dimensions:        (y: 1890, x: 1189)\n",
+       "Coordinates:\n",
+       "    lat            (y, x) float64 18MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    lon            (y, x) float64 18MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "Dimensions without coordinates: y, x\n",
+       "Data variables:\n",
+       "    quality_flags  (y, x) uint32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_3         (y, x) float32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_6         (y, x) float32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_8         (y, x) float32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds = xr.open_zarr(\"./inputdata/S3-OLCI-L2A.zarr.zip\", consolidated=False)\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Geographic 2D CRS: EPSG:4326>\n",
+       "Name: WGS 84\n",
+       "Axis Info [ellipsoidal]:\n",
+       "- Lat[north]: Geodetic latitude (degree)\n",
+       "- Lon[east]: Geodetic longitude (degree)\n",
+       "Area of Use:\n",
+       "- name: World.\n",
+       "- bounds: (-180.0, -90.0, 180.0, 90.0)\n",
+       "Datum: World Geodetic System 1984 ensemble\n",
+       "- Ellipsoid: WGS 84\n",
+       "- Prime Meridian: Greenwich"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crs_4326 = pp.crs.CRS(4326)\n",
+    "crs_4326"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crs_4326.is_geographic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crs_4326.is_geocentric"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Projected CRS: EPSG:32633>\n",
+       "Name: WGS 84 / UTM zone 33N\n",
+       "Axis Info [cartesian]:\n",
+       "- E[east]: Easting (metre)\n",
+       "- N[north]: Northing (metre)\n",
+       "Area of Use:\n",
+       "- name: Between 12°E and 18°E, northern hemisphere between equator and 84°N, onshore and offshore. Austria. Bosnia and Herzegovina. Cameroon. Central African Republic. Chad. Congo. Croatia. Czechia. Democratic Republic of the Congo (Zaire). Gabon. Germany. Hungary. Italy. Libya. Malta. Niger. Nigeria. Norway. Poland. San Marino. Slovakia. Slovenia. Svalbard. Sweden. Vatican City State.\n",
+       "- bounds: (12.0, 0.0, 18.0, 84.0)\n",
+       "Coordinate Operation:\n",
+       "- name: UTM zone 33N\n",
+       "- method: Transverse Mercator\n",
+       "Datum: World Geodetic System 1984 ensemble\n",
+       "- Ellipsoid: WGS 84\n",
+       "- Prime Meridian: Greenwich"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crs_32633 = pp.crs.CRS(32633)\n",
+    "crs_32633"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Conversion Transformer: pipeline>\n",
+       "Description: UTM zone 33N\n",
+       "Area of Use:\n",
+       "- name: Between 12°E and 18°E, northern hemisphere between equator and 84°N, onshore and offshore.\n",
+       "- bounds: (12.0, 0.0, 18.0, 84.0)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t = pp.transformer.Transformer.from_crs(crs_4326, crs_32633)\n",
+    "t"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "lon = ds.lon.values\n",
+    "lat = ds.lat.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 454 ms, sys: 10.1 ms, total: 464 ms\n",
+      "Wall time: 463 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "x, y = t.transform(lat, lon)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[464353.17350437, 464753.99068697, 464753.99068697, ...,\n",
+       "         778366.98327271, 778663.97989779, 778960.82095417],\n",
+       "        [464300.61922255, 464697.86336861, 464697.86336861, ...,\n",
+       "         778311.52553234, 778608.48730308, 778905.40483205],\n",
+       "        [464244.50782782, 464643.5297553 , 464643.5297553 , ...,\n",
+       "         778256.11946402, 778553.04638088, 778849.92904976],\n",
+       "        ...,\n",
+       "        [355582.31759961, 356009.5675282 , 356009.5675282 , ...,\n",
+       "         668917.33742756, 669212.77356855, 669508.22326567],\n",
+       "        [355522.80213548, 355950.07579013, 355950.07579013, ...,\n",
+       "         668857.14267177, 669152.60061632, 669448.00001141],\n",
+       "        [355463.34306198, 355890.64413473, 355890.64413473, ...,\n",
+       "         668796.87484134, 669092.350345  , 669387.77154332]],\n",
+       "       shape=(1890, 1189)),\n",
+       " array([[6722665.0879521 , 6722587.51099095, 6722587.51099095, ...,\n",
+       "         6662383.08675777, 6662325.42149084, 6662267.76727586],\n",
+       "        [6722380.12777498, 6722303.24876914, 6722303.24876914, ...,\n",
+       "         6662095.72015417, 6662038.04563426, 6661980.39060315],\n",
+       "        [6722095.87204537, 6722018.63563135, 6722018.63563135, ...,\n",
+       "         6661808.24764388, 6661750.56387706, 6661692.89959194],\n",
+       "        ...,\n",
+       "        [6186558.12992815, 6186468.08028835, 6186468.08028835, ...,\n",
+       "         6120997.19266252, 6120934.81417697, 6120872.34396918],\n",
+       "        [6186274.18860283, 6186184.02228292, 6186184.02228292, ...,\n",
+       "         6120710.71380218, 6120648.21975818, 6120585.85404474],\n",
+       "        [6185990.24598573, 6185900.07425244, 6185900.07425244, ...,\n",
+       "         6120424.23357397, 6120361.73520792, 6120299.25393304]],\n",
+       "       shape=(1890, 1189)))"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x, y"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 34.29 MiB </td>\n",
+       "                        <td> 4.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2, 1890, 1189) </td>\n",
+       "                        <td> (2, 512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"150\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"32\" x2=\"24\" y2=\"47\" />\n",
+       "  <line x1=\"10\" y1=\"65\" x2=\"24\" y2=\"79\" />\n",
+       "  <line x1=\"10\" y1=\"97\" x2=\"24\" y2=\"112\" />\n",
+       "  <line x1=\"10\" y1=\"120\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,134.9485979497544 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"85\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"100\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"42\" y1=\"0\" x2=\"57\" y2=\"14\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"89\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"100\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 85.4920634920635,0.0 100.4406614418179,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"100\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"47\" x2=\"100\" y2=\"47\" />\n",
+       "  <line x1=\"24\" y1=\"79\" x2=\"100\" y2=\"79\" />\n",
+       "  <line x1=\"24\" y1=\"112\" x2=\"100\" y2=\"112\" />\n",
+       "  <line x1=\"24\" y1=\"134\" x2=\"100\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"57\" y1=\"14\" x2=\"57\" y2=\"134\" />\n",
+       "  <line x1=\"89\" y1=\"14\" x2=\"89\" y2=\"134\" />\n",
+       "  <line x1=\"100\" y1=\"14\" x2=\"100\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 100.4406614418179,14.948597949754403 100.4406614418179,134.9485979497544 24.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"62.694630\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"120.440661\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,120.440661,74.948598)\">1890</text>\n",
+       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">2</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "dask.array<rechunk-merge, shape=(2, 1890, 1189), dtype=float64, chunksize=(2, 512, 512), chunktype=numpy.ndarray>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "coords_4326 = da.stack([ds.lat.data, ds.lon.data]).rechunk((2, None, None))\n",
+    "coords_4326"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def transform(block, t=None):\n",
+    "    x1, y1 = block\n",
+    "    x2, y2 = t.transform(x1, y1)\n",
+    "    return np.stack([x2, y2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 34.29 MiB </td>\n",
+       "                        <td> 4.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2, 1890, 1189) </td>\n",
+       "                        <td> (2, 512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 9 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"150\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"32\" x2=\"24\" y2=\"47\" />\n",
+       "  <line x1=\"10\" y1=\"65\" x2=\"24\" y2=\"79\" />\n",
+       "  <line x1=\"10\" y1=\"97\" x2=\"24\" y2=\"112\" />\n",
+       "  <line x1=\"10\" y1=\"120\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,134.9485979497544 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"85\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"100\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"42\" y1=\"0\" x2=\"57\" y2=\"14\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"89\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"100\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 85.4920634920635,0.0 100.4406614418179,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"100\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"47\" x2=\"100\" y2=\"47\" />\n",
+       "  <line x1=\"24\" y1=\"79\" x2=\"100\" y2=\"79\" />\n",
+       "  <line x1=\"24\" y1=\"112\" x2=\"100\" y2=\"112\" />\n",
+       "  <line x1=\"24\" y1=\"134\" x2=\"100\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"57\" y1=\"14\" x2=\"57\" y2=\"134\" />\n",
+       "  <line x1=\"89\" y1=\"14\" x2=\"89\" y2=\"134\" />\n",
+       "  <line x1=\"100\" y1=\"14\" x2=\"100\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 100.4406614418179,14.948597949754403 100.4406614418179,134.9485979497544 24.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"62.694630\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"120.440661\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,120.440661,74.948598)\">1890</text>\n",
+       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">2</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "dask.array<transpose, shape=(2, 1890, 1189), dtype=float64, chunksize=(2, 512, 512), chunktype=numpy.ndarray>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "coords_32633 = da.apply_gufunc(\n",
+    "    transform, \"()->()\", coords_4326, output_dtypes=np.float64, t=t\n",
+    ")\n",
+    "coords_32633"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 955 ms, sys: 107 ms, total: 1.06 s\n",
+      "Wall time: 343 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "x, y = coords_32633.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[464353.17350437, 464753.99068697, 464753.99068697, ...,\n",
+       "         778366.98327271, 778663.97989779, 778960.82095417],\n",
+       "        [464300.61922255, 464697.86336861, 464697.86336861, ...,\n",
+       "         778311.52553234, 778608.48730308, 778905.40483205],\n",
+       "        [464244.50782782, 464643.5297553 , 464643.5297553 , ...,\n",
+       "         778256.11946402, 778553.04638088, 778849.92904976],\n",
+       "        ...,\n",
+       "        [355582.31759961, 356009.5675282 , 356009.5675282 , ...,\n",
+       "         668917.33742756, 669212.77356855, 669508.22326567],\n",
+       "        [355522.80213548, 355950.07579013, 355950.07579013, ...,\n",
+       "         668857.14267177, 669152.60061632, 669448.00001141],\n",
+       "        [355463.34306198, 355890.64413473, 355890.64413473, ...,\n",
+       "         668796.87484134, 669092.350345  , 669387.77154332]],\n",
+       "       shape=(1890, 1189)),\n",
+       " array([[6722665.0879521 , 6722587.51099095, 6722587.51099095, ...,\n",
+       "         6662383.08675777, 6662325.42149084, 6662267.76727586],\n",
+       "        [6722380.12777498, 6722303.24876914, 6722303.24876914, ...,\n",
+       "         6662095.72015417, 6662038.04563426, 6661980.39060315],\n",
+       "        [6722095.87204537, 6722018.63563135, 6722018.63563135, ...,\n",
+       "         6661808.24764388, 6661750.56387706, 6661692.89959194],\n",
+       "        ...,\n",
+       "        [6186558.12992815, 6186468.08028835, 6186468.08028835, ...,\n",
+       "         6120997.19266252, 6120934.81417697, 6120872.34396918],\n",
+       "        [6186274.18860283, 6186184.02228292, 6186184.02228292, ...,\n",
+       "         6120710.71380218, 6120648.21975818, 6120585.85404474],\n",
+       "        [6185990.24598573, 6185900.07425244, 6185900.07425244, ...,\n",
+       "         6120424.23357397, 6120361.73520792, 6120299.25393304]],\n",
+       "       shape=(1890, 1189)))"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x, y"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def transform2(x1, y1, t=None):\n",
+    "    x2, y2 = t.transform(x1, y1)\n",
+    "    return x2, y2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(dask.array<transpose, shape=(1890, 1189), dtype=float64, chunksize=(512, 512), chunktype=numpy.ndarray>,\n",
+       " dask.array<transpose, shape=(1890, 1189), dtype=float64, chunksize=(512, 512), chunktype=numpy.ndarray>)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x, y = da.apply_gufunc(\n",
+    "    transform2,\n",
+    "    \"(),()->(),()\",\n",
+    "    ds.lat.data,\n",
+    "    ds.lon.data,\n",
+    "    output_dtypes=(np.float64, np.float64),\n",
+    "    t=t,\n",
+    ")\n",
+    "x, y"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 1.69 s, sys: 64.8 ms, total: 1.76 s\n",
+      "Wall time: 570 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "xx = x.compute()\n",
+    "yy = y.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[464353.17350437, 464753.99068697, 464753.99068697, ...,\n",
+       "         778366.98327271, 778663.97989779, 778960.82095417],\n",
+       "        [464300.61922255, 464697.86336861, 464697.86336861, ...,\n",
+       "         778311.52553234, 778608.48730308, 778905.40483205],\n",
+       "        [464244.50782782, 464643.5297553 , 464643.5297553 , ...,\n",
+       "         778256.11946402, 778553.04638088, 778849.92904976],\n",
+       "        ...,\n",
+       "        [355582.31759961, 356009.5675282 , 356009.5675282 , ...,\n",
+       "         668917.33742756, 669212.77356855, 669508.22326567],\n",
+       "        [355522.80213548, 355950.07579013, 355950.07579013, ...,\n",
+       "         668857.14267177, 669152.60061632, 669448.00001141],\n",
+       "        [355463.34306198, 355890.64413473, 355890.64413473, ...,\n",
+       "         668796.87484134, 669092.350345  , 669387.77154332]],\n",
+       "       shape=(1890, 1189)),\n",
+       " array([[6722665.0879521 , 6722587.51099095, 6722587.51099095, ...,\n",
+       "         6662383.08675777, 6662325.42149084, 6662267.76727586],\n",
+       "        [6722380.12777498, 6722303.24876914, 6722303.24876914, ...,\n",
+       "         6662095.72015417, 6662038.04563426, 6661980.39060315],\n",
+       "        [6722095.87204537, 6722018.63563135, 6722018.63563135, ...,\n",
+       "         6661808.24764388, 6661750.56387706, 6661692.89959194],\n",
+       "        ...,\n",
+       "        [6186558.12992815, 6186468.08028835, 6186468.08028835, ...,\n",
+       "         6120997.19266252, 6120934.81417697, 6120872.34396918],\n",
+       "        [6186274.18860283, 6186184.02228292, 6186184.02228292, ...,\n",
+       "         6120710.71380218, 6120648.21975818, 6120585.85404474],\n",
+       "        [6185990.24598573, 6185900.07425244, 6185900.07425244, ...,\n",
+       "         6120424.23357397, 6120361.73520792, 6120299.25393304]],\n",
+       "       shape=(1890, 1189)))"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xx, yy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Geographic 2D CRS: OGC:CRS84>\n",
+       "Name: WGS 84 (CRS84)\n",
+       "Axis Info [ellipsoidal]:\n",
+       "- Lon[east]: Geodetic longitude (degree)\n",
+       "- Lat[north]: Geodetic latitude (degree)\n",
+       "Area of Use:\n",
+       "- name: World.\n",
+       "- bounds: (-180.0, -90.0, 180.0, 90.0)\n",
+       "Datum: World Geodetic System 1984 ensemble\n",
+       "- Ellipsoid: WGS 84\n",
+       "- Prime Meridian: Greenwich"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pp.crs.CRS.from_string(\"urn:ogc:def:crs:OGC:1.3:CRS84\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Geographic 2D CRS: EPSG:4326>\n",
+       "Name: WGS 84\n",
+       "Axis Info [ellipsoidal]:\n",
+       "- Lat[north]: Geodetic latitude (degree)\n",
+       "- Lon[east]: Geodetic longitude (degree)\n",
+       "Area of Use:\n",
+       "- name: World.\n",
+       "- bounds: (-180.0, -90.0, 180.0, 90.0)\n",
+       "Datum: World Geodetic System 1984 ensemble\n",
+       "- Ellipsoid: WGS 84\n",
+       "- Prime Meridian: Greenwich"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pp.crs.CRS.from_user_input(\"epsg:4326\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/examples/rectify_sentinel3.ipynb b/docs/examples/rectify_sentinel3.ipynb
new file mode 100644
index 0000000..59e8ec7
--- /dev/null
+++ b/docs/examples/rectify_sentinel3.ipynb
@@ -0,0 +1,3475 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Rectification to a Sentinel-3 OLCI scene\n",
+    "\n",
+    "In this notebook, we apply the rectification algorithm to a Setninel-3 OLCI Level-1b scene. The Sentinel-3 OLCI Level-1b product comes with **2D coordinates** – irregular grids where each pixel has its own pair of x/y orlat/lon coordinates. We will there rectify the dataset to a regular grid. \n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "from xcube_resampling.rectify import rectify_dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 116 ms, sys: 15.9 ms, total: 132 ms\n",
+      "Wall time: 151 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 72MB\n",
+       "Dimensions:        (y: 1890, x: 1189)\n",
+       "Coordinates:\n",
+       "    lat            (y, x) float64 18MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    lon            (y, x) float64 18MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: y, x\n",
+       "Data variables:\n",
+       "    quality_flags  (y, x) uint32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_3         (y, x) float32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_6         (y, x) float32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_8         (y, x) float32 9MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-dcb11534-d8fd-4bbb-bd39-abfe9c779f35' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dcb11534-d8fd-4bbb-bd39-abfe9c779f35' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 1890</li><li><span>x</span>: 1189</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ed5b5ae5-44af-42cb-aa02-63fbb41e7c8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ed5b5ae5-44af-42cb-aa02-63fbb41e7c8f' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-fb6e08e3-4ac9-468c-8321-452f0a1f4378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb6e08e3-4ac9-468c-8321-452f0a1f4378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baea2a6b-3da5-4121-bbc9-9bed6b78f7be' class='xr-var-data-in' type='checkbox'><label for='data-baea2a6b-3da5-4121-bbc9-9bed6b78f7be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 17.14 MiB </td>\n",
+       "                        <td> 2.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-819edf61-c5a3-4ae8-81d0-ca7af31dec01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-819edf61-c5a3-4ae8-81d0-ca7af31dec01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d711e26-5e0e-4f57-847c-1e60a053fd5a' class='xr-var-data-in' type='checkbox'><label for='data-6d711e26-5e0e-4f57-847c-1e60a053fd5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 17.14 MiB </td>\n",
+       "                        <td> 2.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ca03a0a2-f96b-466a-b937-7e2103cb5ac5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca03a0a2-f96b-466a-b937-7e2103cb5ac5' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>quality_flags</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-e2e9f537-f5c6-4ccf-a065-e1c73f933a81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2e9f537-f5c6-4ccf-a065-e1c73f933a81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcecef2f-e1c5-4f07-81c6-557d9e62dbab' class='xr-var-data-in' type='checkbox'><label for='data-fcecef2f-e1c5-4f07-81c6-557d9e62dbab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_coding_name :</span></dt><dd>quality_flags</dd><dt><span>flag_descriptions :</span></dt><dd></dd><dt><span>flag_masks :</span></dt><dd>[-2147483648, 1073741824, 536870912, 268435456, 134217728, 67108864, 33554432, 16777216, 8388608, 4194304, 2097152, 1048576, 524288, 262144, 131072, 65536, 32768, 16384, 8192, 4096, 2048, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1]</dd><dt><span>flag_meanings :</span></dt><dd>land coastline fresh_inland_water tidal_region bright straylight_risk invalid cosmetic duplicated sun_glint_risk dubious saturated_Oa01 saturated_Oa02 saturated_Oa03 saturated_Oa04 saturated_Oa05 saturated_Oa06 saturated_Oa07 saturated_Oa08 saturated_Oa09 saturated_Oa10 saturated_Oa11 saturated_Oa12 saturated_Oa13 saturated_Oa14 saturated_Oa15 saturated_Oa16 saturated_Oa17 saturated_Oa18 saturated_Oa19 saturated_Oa20 saturated_Oa21</dd><dt><span>long_name :</span></dt><dd>Classification and quality flags</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_3</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-a2b01b91-15cc-43d1-9950-f994f143e1fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2b01b91-15cc-43d1-9950-f994f143e1fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a170ee1-4344-44df-ae36-27de74d08c7d' class='xr-var-data-in' type='checkbox'><label for='data-2a170ee1-4344-44df-ae36-27de74d08c7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>2.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>442.5</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_6</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-9eff375c-bfdf-4b32-8432-07361fecb199' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9eff375c-bfdf-4b32-8432-07361fecb199' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0faac561-48d8-4216-a9d8-12ac76828680' class='xr-var-data-in' type='checkbox'><label for='data-0faac561-48d8-4216-a9d8-12ac76828680' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>5.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>560.0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_8</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-59621985-08b8-420c-af17-cde8990db65c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59621985-08b8-420c-af17-cde8990db65c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2008c075-3de4-407b-a51f-e6d8fefbcfcb' class='xr-var-data-in' type='checkbox'><label for='data-2008c075-3de4-407b-a51f-e6d8fefbcfcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>7.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>665.0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8.57 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1890, 1189) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"32\" x2=\"75\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"75\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"75\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"32\" y1=\"0\" x2=\"32\" y2=\"120\" />\n",
+       "  <line x1=\"65\" y1=\"0\" x2=\"65\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.4920634920635,0.0 75.4920634920635,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.746032\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1189</text>\n",
+       "  <text x=\"95.492063\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.492063,60.000000)\">1890</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-3e9f84d3-ed89-4338-bf1b-a57d7dbbf69a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3e9f84d3-ed89-4338-bf1b-a57d7dbbf69a' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-80bd6f01-6b37-4a44-be18-8c8cb3c9032c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-80bd6f01-6b37-4a44-be18-8c8cb3c9032c' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>product_type :</span></dt><dd>C2RCC_OLCI</dd><dt><span>start_date :</span></dt><dd>04-JUL-2018 09:21:55.677316</dd><dt><span>stop_date :</span></dt><dd>04-JUL-2018 09:23:18.811790</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 72MB\n",
+       "Dimensions:        (y: 1890, x: 1189)\n",
+       "Coordinates:\n",
+       "    lat            (y, x) float64 18MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    lon            (y, x) float64 18MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "Dimensions without coordinates: y, x\n",
+       "Data variables:\n",
+       "    quality_flags  (y, x) uint32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_3         (y, x) float32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_6         (y, x) float32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_8         (y, x) float32 9MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "source_ds = xr.open_zarr(\"./inputdata/S3-OLCI-L2A.zarr.zip\", consolidated=False)\n",
+    "source_ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The provided coordinates, latitude (`lat`) and longitude (`lon`), are *terrain-corrected* \n",
+    "using a digital elevation model (DEM) that approximates the Earth's actual fractal \n",
+    "surface. As a result, the gradient vectors do not vary monotonically across the scene. Instead, \n",
+    "they reflect the surface roughness captured by the DEM. Areas of high terrain \n",
+    "variability are highlighted in the right figure below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 893 ms, sys: 198 ms, total: 1.09 s\n",
+      "Wall time: 979 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x760b10ebc910>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1400x500 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "lon_grad = source_ds.lat.differentiate(\"y\").rename(\"Vertical Gradient\")\n",
+    "\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(14, 5))\n",
+    "source_ds.rtoa_8.plot(ax=ax[0], cmap=\"gray\", vmax=0.2)\n",
+    "lon_grad.plot(ax=ax[1], cmap=\"viridis\", robust=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we can rectify the dataset. Note that this can be done with the `resample_in_space` method. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2.42 s, sys: 165 ms, total: 2.59 s\n",
+      "Wall time: 1.38 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 102MB\n",
+       "Dimensions:        (lon: 2926, lat: 2177)\n",
+       "Coordinates:\n",
+       "    spatial_ref    int64 8B 0\n",
+       "  * lon            (lon) float64 23kB 12.69 12.7 12.7 12.7 ... 20.0 20.0 20.01\n",
+       "  * lat            (lat) float64 17kB 60.64 60.64 60.64 ... 55.21 55.2 55.2\n",
+       "Data variables:\n",
+       "    quality_flags  (lat, lon) uint32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_3         (lat, lon) float32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_6         (lat, lon) float32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_8         (lat, lon) float32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-db5a83c8-e525-4819-bd3c-5e45f45e49df' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-db5a83c8-e525-4819-bd3c-5e45f45e49df' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 2926</li><li><span class='xr-has-index'>lat</span>: 2177</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fbb30691-fe15-4682-9fba-cc8a2a49261c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fbb30691-fe15-4682-9fba-cc8a2a49261c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-47b81e1e-73fb-4ebf-94ed-4195b2b73e5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47b81e1e-73fb-4ebf-94ed-4195b2b73e5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-406230f5-fb3c-4190-a4d4-664546b8bbdb' class='xr-var-data-in' type='checkbox'><label for='data-406230f5-fb3c-4190-a4d4-664546b8bbdb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],CS[ellipsoidal,2],AXIS[&quot;geodetic latitude (Lat)&quot;,north,ORDER[1],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],AXIS[&quot;geodetic longitude (Lon)&quot;,east,ORDER[2],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],USAGE[SCOPE[&quot;Horizontal component of 3D system.&quot;],AREA[&quot;World.&quot;],BBOX[-90,-180,90,180]],ID[&quot;EPSG&quot;,4326]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984 ensemble</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>12.69 12.7 12.7 ... 20.0 20.0 20.01</div><input id='attrs-4ff9914e-6653-4a2a-b63e-ce146b20d59b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ff9914e-6653-4a2a-b63e-ce146b20d59b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d049ac9-b44d-4b07-b31d-650a8d25303b' class='xr-var-data-in' type='checkbox'><label for='data-4d049ac9-b44d-4b07-b31d-650a8d25303b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([12.694301, 12.696801, 12.699301, ..., 20.001801, 20.004301, 20.006801],\n",
+       "      shape=(2926,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>60.64 60.64 60.64 ... 55.2 55.2</div><input id='attrs-a34dd1b9-f18f-4ed5-865a-0a495932289f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a34dd1b9-f18f-4ed5-865a-0a495932289f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b0c7d50-7e81-4497-a5c3-350c0fd9a406' class='xr-var-data-in' type='checkbox'><label for='data-6b0c7d50-7e81-4497-a5c3-350c0fd9a406' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([60.64018, 60.63768, 60.63518, ..., 55.20518, 55.20268, 55.20018],\n",
+       "      shape=(2177,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30c8bed1-d8f1-474d-8cf5-a7ec53a68ef7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30c8bed1-d8f1-474d-8cf5-a7ec53a68ef7' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>quality_flags</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-389c4b40-07e1-4ffb-bc55-f8f247adc6c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-389c4b40-07e1-4ffb-bc55-f8f247adc6c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fe60038-611c-45e5-8670-9b0c5ca7ee8e' class='xr-var-data-in' type='checkbox'><label for='data-6fe60038-611c-45e5-8670-9b0c5ca7ee8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_coding_name :</span></dt><dd>quality_flags</dd><dt><span>flag_descriptions :</span></dt><dd></dd><dt><span>flag_masks :</span></dt><dd>[-2147483648, 1073741824, 536870912, 268435456, 134217728, 67108864, 33554432, 16777216, 8388608, 4194304, 2097152, 1048576, 524288, 262144, 131072, 65536, 32768, 16384, 8192, 4096, 2048, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1]</dd><dt><span>flag_meanings :</span></dt><dd>land coastline fresh_inland_water tidal_region bright straylight_risk invalid cosmetic duplicated sun_glint_risk dubious saturated_Oa01 saturated_Oa02 saturated_Oa03 saturated_Oa04 saturated_Oa05 saturated_Oa06 saturated_Oa07 saturated_Oa08 saturated_Oa09 saturated_Oa10 saturated_Oa11 saturated_Oa12 saturated_Oa13 saturated_Oa14 saturated_Oa15 saturated_Oa16 saturated_Oa17 saturated_Oa18 saturated_Oa19 saturated_Oa20 saturated_Oa21</dd><dt><span>long_name :</span></dt><dd>Classification and quality flags</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_3</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-2fb28057-5a7b-45f6-a91f-f1a63a9559c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fb28057-5a7b-45f6-a91f-f1a63a9559c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7da47f0-abc8-4788-89b9-14b5126c4559' class='xr-var-data-in' type='checkbox'><label for='data-c7da47f0-abc8-4788-89b9-14b5126c4559' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>2.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>442.5</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_6</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-4ab6d03d-de0a-450a-be45-aaff9bf03535' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ab6d03d-de0a-450a-be45-aaff9bf03535' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4696c833-a4ba-4dc8-a1f3-a5309bbf1e38' class='xr-var-data-in' type='checkbox'><label for='data-4696c833-a4ba-4dc8-a1f3-a5309bbf1e38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>5.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>560.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_8</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-2ce23cd6-4453-41d4-a0d8-212f6a55401c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ce23cd6-4453-41d4-a0d8-212f6a55401c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12f343ef-268e-468d-b9e4-781cad41bd93' class='xr-var-data-in' type='checkbox'><label for='data-12f343ef-268e-468d-b9e4-781cad41bd93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>7.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>665.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5df809b-6601-4f26-9af3-273c35b35fdf' class='xr-section-summary-in' type='checkbox'  ><label for='section-a5df809b-6601-4f26-9af3-273c35b35fdf' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b6005907-4aa3-40e7-8623-5cd8429b9df7' class='xr-index-data-in' type='checkbox'/><label for='index-b6005907-4aa3-40e7-8623-5cd8429b9df7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([         12.694301, 12.696800999999999,          12.699301,\n",
+       "                12.701801,          12.704301, 12.706800999999999,\n",
+       "                12.709301,          12.711801, 12.714300999999999,\n",
+       "                12.716801,\n",
+       "       ...\n",
+       "                19.984301,          19.986801, 19.989300999999998,\n",
+       "                19.991801,          19.994301, 19.996800999999998,\n",
+       "                19.999301,          20.001801, 20.004300999999998,\n",
+       "                20.006801],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2926))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d86c0d8f-4a41-4538-b0b8-119a8d208b5c' class='xr-index-data-in' type='checkbox'/><label for='index-d86c0d8f-4a41-4538-b0b8-119a8d208b5c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([          60.64018,           60.63768,           60.63518,\n",
+       "                 60.63268,           60.63018,           60.62768,\n",
+       "                 60.62518,           60.62268,           60.62018,\n",
+       "                 60.61768,\n",
+       "       ...\n",
+       "                 55.22268,           55.22018, 55.217679999999994,\n",
+       "                 55.21518,           55.21268, 55.210179999999994,\n",
+       "       55.207679999999996,           55.20518, 55.202679999999994,\n",
+       "       55.200179999999996],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2177))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c68ad45-03e5-4a74-a587-4f5d7df9ac22' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9c68ad45-03e5-4a74-a587-4f5d7df9ac22' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>product_type :</span></dt><dd>C2RCC_OLCI</dd><dt><span>start_date :</span></dt><dd>04-JUL-2018 09:21:55.677316</dd><dt><span>stop_date :</span></dt><dd>04-JUL-2018 09:23:18.811790</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 102MB\n",
+       "Dimensions:        (lon: 2926, lat: 2177)\n",
+       "Coordinates:\n",
+       "    spatial_ref    int64 8B 0\n",
+       "  * lon            (lon) float64 23kB 12.69 12.7 12.7 12.7 ... 20.0 20.0 20.01\n",
+       "  * lat            (lat) float64 17kB 60.64 60.64 60.64 ... 55.21 55.2 55.2\n",
+       "Data variables:\n",
+       "    quality_flags  (lat, lon) uint32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_3         (lat, lon) float32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_6         (lat, lon) float32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_8         (lat, lon) float32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "target_ds = rectify_dataset(source_ds, interp_methods=\"nearest\")\n",
+    "target_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2.33 s, sys: 384 ms, total: 2.72 s\n",
+      "Wall time: 1.51 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x760b104c3ed0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "target_ds.rtoa_8.plot(cmap=\"gray\", vmax=0.2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can also change the chunk size in the output dataset with the keyword argument `tile_size`. Note that `interp_methods=0` is identical to `interp_methods=\"nearest\"`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2.17 s, sys: 123 ms, total: 2.29 s\n",
+      "Wall time: 1.4 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 102MB\n",
+       "Dimensions:        (lon: 2926, lat: 2177)\n",
+       "Coordinates:\n",
+       "    spatial_ref    int64 8B 0\n",
+       "  * lon            (lon) float64 23kB 12.69 12.7 12.7 12.7 ... 20.0 20.0 20.01\n",
+       "  * lat            (lat) float64 17kB 60.64 60.64 60.64 ... 55.21 55.2 55.2\n",
+       "Data variables:\n",
+       "    quality_flags  (lat, lon) uint32 25MB dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;\n",
+       "    rtoa_3         (lat, lon) float32 25MB dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;\n",
+       "    rtoa_6         (lat, lon) float32 25MB dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;\n",
+       "    rtoa_8         (lat, lon) float32 25MB dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6aa7155f-3773-4846-ab53-6bd3e94c3d7f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6aa7155f-3773-4846-ab53-6bd3e94c3d7f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 2926</li><li><span class='xr-has-index'>lat</span>: 2177</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b198653a-b066-4702-af67-0a62ac6a5022' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b198653a-b066-4702-af67-0a62ac6a5022' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-63243e8c-52ef-4ee1-91f7-744a146e0bce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63243e8c-52ef-4ee1-91f7-744a146e0bce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e662066b-f5a2-4311-84da-fff173c833bb' class='xr-var-data-in' type='checkbox'><label for='data-e662066b-f5a2-4311-84da-fff173c833bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],CS[ellipsoidal,2],AXIS[&quot;geodetic latitude (Lat)&quot;,north,ORDER[1],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],AXIS[&quot;geodetic longitude (Lon)&quot;,east,ORDER[2],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],USAGE[SCOPE[&quot;Horizontal component of 3D system.&quot;],AREA[&quot;World.&quot;],BBOX[-90,-180,90,180]],ID[&quot;EPSG&quot;,4326]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984 ensemble</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>12.69 12.7 12.7 ... 20.0 20.0 20.01</div><input id='attrs-f9060483-c297-4b96-9499-f77dd923d3e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9060483-c297-4b96-9499-f77dd923d3e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d3066eb-6d73-4d7f-9567-979250a518ce' class='xr-var-data-in' type='checkbox'><label for='data-3d3066eb-6d73-4d7f-9567-979250a518ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([12.694301, 12.696801, 12.699301, ..., 20.001801, 20.004301, 20.006801],\n",
+       "      shape=(2926,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>60.64 60.64 60.64 ... 55.2 55.2</div><input id='attrs-4a6fd33a-0b60-4b1b-add2-95a0fd1087e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a6fd33a-0b60-4b1b-add2-95a0fd1087e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abe30309-2ccf-4192-8f58-a3c942d0ee0d' class='xr-var-data-in' type='checkbox'><label for='data-abe30309-2ccf-4192-8f58-a3c942d0ee0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([60.64018, 60.63768, 60.63518, ..., 55.20518, 55.20268, 55.20018],\n",
+       "      shape=(2177,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c7ab2a4e-4a5d-45c6-b5c6-d695922fe0e6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c7ab2a4e-4a5d-45c6-b5c6-d695922fe0e6' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>quality_flags</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-5d62036d-656b-4e66-8fe5-ac5418a38496' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d62036d-656b-4e66-8fe5-ac5418a38496' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3abab1fc-fd99-4b97-891c-97d9a39d97dc' class='xr-var-data-in' type='checkbox'><label for='data-3abab1fc-fd99-4b97-891c-97d9a39d97dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_coding_name :</span></dt><dd>quality_flags</dd><dt><span>flag_descriptions :</span></dt><dd></dd><dt><span>flag_masks :</span></dt><dd>[-2147483648, 1073741824, 536870912, 268435456, 134217728, 67108864, 33554432, 16777216, 8388608, 4194304, 2097152, 1048576, 524288, 262144, 131072, 65536, 32768, 16384, 8192, 4096, 2048, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1]</dd><dt><span>flag_meanings :</span></dt><dd>land coastline fresh_inland_water tidal_region bright straylight_risk invalid cosmetic duplicated sun_glint_risk dubious saturated_Oa01 saturated_Oa02 saturated_Oa03 saturated_Oa04 saturated_Oa05 saturated_Oa06 saturated_Oa07 saturated_Oa08 saturated_Oa09 saturated_Oa10 saturated_Oa11 saturated_Oa12 saturated_Oa13 saturated_Oa14 saturated_Oa15 saturated_Oa16 saturated_Oa17 saturated_Oa18 saturated_Oa19 saturated_Oa20 saturated_Oa21</dd><dt><span>long_name :</span></dt><dd>Classification and quality flags</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 16.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (2048, 2048) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 4 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_3</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-923ae110-7f8d-4e1a-bf63-5f2e1e8a48a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-923ae110-7f8d-4e1a-bf63-5f2e1e8a48a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-944ed080-9b23-4618-83f4-cd3d8cb73af0' class='xr-var-data-in' type='checkbox'><label for='data-944ed080-9b23-4618-83f4-cd3d8cb73af0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>2.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>442.5</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 16.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (2048, 2048) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 4 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_6</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-a63c7026-1caa-4d21-9b3d-cb85eb41652a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a63c7026-1caa-4d21-9b3d-cb85eb41652a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2ce43ac-e038-4b17-9f0f-d0f4ad7c24f9' class='xr-var-data-in' type='checkbox'><label for='data-e2ce43ac-e038-4b17-9f0f-d0f4ad7c24f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>5.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>560.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 16.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (2048, 2048) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 4 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_8</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2048, 2048), meta=np.ndarray&gt;</div><input id='attrs-9949de9f-f469-47b3-bfe9-45095c5dba68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9949de9f-f469-47b3-bfe9-45095c5dba68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-231d4414-a27e-49dd-b199-25d76790adf8' class='xr-var-data-in' type='checkbox'><label for='data-231d4414-a27e-49dd-b199-25d76790adf8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>7.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>665.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 16.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (2048, 2048) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 4 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d38c28ab-641d-4f0b-b7e7-8e35c653e583' class='xr-section-summary-in' type='checkbox'  ><label for='section-d38c28ab-641d-4f0b-b7e7-8e35c653e583' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1034a5e0-281d-4fa3-807f-b956b07db94c' class='xr-index-data-in' type='checkbox'/><label for='index-1034a5e0-281d-4fa3-807f-b956b07db94c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([         12.694301, 12.696800999999999,          12.699301,\n",
+       "                12.701801,          12.704301, 12.706800999999999,\n",
+       "                12.709301,          12.711801, 12.714300999999999,\n",
+       "                12.716801,\n",
+       "       ...\n",
+       "                19.984301,          19.986801, 19.989300999999998,\n",
+       "                19.991801,          19.994301, 19.996800999999998,\n",
+       "                19.999301,          20.001801, 20.004300999999998,\n",
+       "                20.006801],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2926))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-5fe7b40f-1cc6-41d2-a767-011dc2f2345d' class='xr-index-data-in' type='checkbox'/><label for='index-5fe7b40f-1cc6-41d2-a767-011dc2f2345d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([          60.64018,           60.63768,           60.63518,\n",
+       "                 60.63268,           60.63018,           60.62768,\n",
+       "                 60.62518,           60.62268,           60.62018,\n",
+       "                 60.61768,\n",
+       "       ...\n",
+       "                 55.22268,           55.22018, 55.217679999999994,\n",
+       "                 55.21518,           55.21268, 55.210179999999994,\n",
+       "       55.207679999999996,           55.20518, 55.202679999999994,\n",
+       "       55.200179999999996],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2177))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6303af1e-95e0-4bfc-b606-628540994f1c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6303af1e-95e0-4bfc-b606-628540994f1c' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>product_type :</span></dt><dd>C2RCC_OLCI</dd><dt><span>start_date :</span></dt><dd>04-JUL-2018 09:21:55.677316</dd><dt><span>stop_date :</span></dt><dd>04-JUL-2018 09:23:18.811790</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 102MB\n",
+       "Dimensions:        (lon: 2926, lat: 2177)\n",
+       "Coordinates:\n",
+       "    spatial_ref    int64 8B 0\n",
+       "  * lon            (lon) float64 23kB 12.69 12.7 12.7 12.7 ... 20.0 20.0 20.01\n",
+       "  * lat            (lat) float64 17kB 60.64 60.64 60.64 ... 55.21 55.2 55.2\n",
+       "Data variables:\n",
+       "    quality_flags  (lat, lon) uint32 25MB dask.array<chunksize=(2048, 2048), meta=np.ndarray>\n",
+       "    rtoa_3         (lat, lon) float32 25MB dask.array<chunksize=(2048, 2048), meta=np.ndarray>\n",
+       "    rtoa_6         (lat, lon) float32 25MB dask.array<chunksize=(2048, 2048), meta=np.ndarray>\n",
+       "    rtoa_8         (lat, lon) float32 25MB dask.array<chunksize=(2048, 2048), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "target_ds = rectify_dataset(source_ds, interp_methods=0, tile_size=2048)\n",
+    "target_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 1.5 s, sys: 167 ms, total: 1.67 s\n",
+      "Wall time: 1.31 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x760b1009e710>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "target_ds.rtoa_8.plot(cmap=\"gray\", vmax=0.2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also apply a different interpolation method, as shown in the next cell. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2.16 s, sys: 126 ms, total: 2.29 s\n",
+      "Wall time: 1.29 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 102MB\n",
+       "Dimensions:        (lon: 2926, lat: 2177)\n",
+       "Coordinates:\n",
+       "    spatial_ref    int64 8B 0\n",
+       "  * lon            (lon) float64 23kB 12.69 12.7 12.7 12.7 ... 20.0 20.0 20.01\n",
+       "  * lat            (lat) float64 17kB 60.64 60.64 60.64 ... 55.21 55.2 55.2\n",
+       "Data variables:\n",
+       "    quality_flags  (lat, lon) uint32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_3         (lat, lon) float32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_6         (lat, lon) float32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "    rtoa_8         (lat, lon) float32 25MB dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-25957f5d-5a45-4c17-82bf-6bb73e75f528' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25957f5d-5a45-4c17-82bf-6bb73e75f528' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 2926</li><li><span class='xr-has-index'>lat</span>: 2177</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1493fdf6-97f4-4401-ab62-968e379803d4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1493fdf6-97f4-4401-ab62-968e379803d4' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-beab207f-68d4-4475-ba4c-06bb9044dd32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-beab207f-68d4-4475-ba4c-06bb9044dd32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa967f93-9f12-421b-9c1c-74ae1fc6fe7c' class='xr-var-data-in' type='checkbox'><label for='data-fa967f93-9f12-421b-9c1c-74ae1fc6fe7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>GEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],CS[ellipsoidal,2],AXIS[&quot;geodetic latitude (Lat)&quot;,north,ORDER[1],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],AXIS[&quot;geodetic longitude (Lon)&quot;,east,ORDER[2],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],USAGE[SCOPE[&quot;Horizontal component of 3D system.&quot;],AREA[&quot;World.&quot;],BBOX[-90,-180,90,180]],ID[&quot;EPSG&quot;,4326]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984 ensemble</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>12.69 12.7 12.7 ... 20.0 20.0 20.01</div><input id='attrs-d5924ebe-a437-4bed-be83-89e7322e9a44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5924ebe-a437-4bed-be83-89e7322e9a44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-965b1e77-c03b-4114-aa2d-e4f0f1d3fbd3' class='xr-var-data-in' type='checkbox'><label for='data-965b1e77-c03b-4114-aa2d-e4f0f1d3fbd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([12.694301, 12.696801, 12.699301, ..., 20.001801, 20.004301, 20.006801],\n",
+       "      shape=(2926,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>60.64 60.64 60.64 ... 55.2 55.2</div><input id='attrs-c6858b04-319a-4d3a-9c13-8916e713784d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6858b04-319a-4d3a-9c13-8916e713784d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15bb0e74-82f5-4a62-b223-85da916262fc' class='xr-var-data-in' type='checkbox'><label for='data-15bb0e74-82f5-4a62-b223-85da916262fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([60.64018, 60.63768, 60.63518, ..., 55.20518, 55.20268, 55.20018],\n",
+       "      shape=(2177,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9278d43c-b884-4e22-a164-c5ea0c58bac7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9278d43c-b884-4e22-a164-c5ea0c58bac7' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>quality_flags</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-3b866c83-457c-4a03-af7a-0220665da7e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b866c83-457c-4a03-af7a-0220665da7e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b4f78d3-b77e-4761-8d6a-8e9170c42ff6' class='xr-var-data-in' type='checkbox'><label for='data-9b4f78d3-b77e-4761-8d6a-8e9170c42ff6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_coding_name :</span></dt><dd>quality_flags</dd><dt><span>flag_descriptions :</span></dt><dd></dd><dt><span>flag_masks :</span></dt><dd>[-2147483648, 1073741824, 536870912, 268435456, 134217728, 67108864, 33554432, 16777216, 8388608, 4194304, 2097152, 1048576, 524288, 262144, 131072, 65536, 32768, 16384, 8192, 4096, 2048, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1]</dd><dt><span>flag_meanings :</span></dt><dd>land coastline fresh_inland_water tidal_region bright straylight_risk invalid cosmetic duplicated sun_glint_risk dubious saturated_Oa01 saturated_Oa02 saturated_Oa03 saturated_Oa04 saturated_Oa05 saturated_Oa06 saturated_Oa07 saturated_Oa08 saturated_Oa09 saturated_Oa10 saturated_Oa11 saturated_Oa12 saturated_Oa13 saturated_Oa14 saturated_Oa15 saturated_Oa16 saturated_Oa17 saturated_Oa18 saturated_Oa19 saturated_Oa20 saturated_Oa21</dd><dt><span>long_name :</span></dt><dd>Classification and quality flags</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_3</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-bc711ec2-5279-427e-b37f-7e85d14b34ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc711ec2-5279-427e-b37f-7e85d14b34ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84bbc5a6-ea5e-4f07-9cae-45dfde2cf4fa' class='xr-var-data-in' type='checkbox'><label for='data-84bbc5a6-ea5e-4f07-9cae-45dfde2cf4fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>2.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>442.5</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_6</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-41f1c627-117d-40f9-b817-212b6f885c49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41f1c627-117d-40f9-b817-212b6f885c49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96f4a96e-5461-40b6-88c5-792270dc6d0b' class='xr-var-data-in' type='checkbox'><label for='data-96f4a96e-5461-40b6-88c5-792270dc6d0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>5.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>560.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtoa_8</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(512, 512), meta=np.ndarray&gt;</div><input id='attrs-da2412cd-a697-4905-898b-bc7b87b14e19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da2412cd-a697-4905-898b-bc7b87b14e19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c1130e8-5a6f-4d2f-95b8-3e8e603bd31f' class='xr-var-data-in' type='checkbox'><label for='data-9c1130e8-5a6f-4d2f-95b8-3e8e603bd31f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bandwidth :</span></dt><dd>10.0</dd><dt><span>long_name :</span></dt><dd>Top-of-atmosphere reflectance</dd><dt><span>spectral_band_index :</span></dt><dd>7.0</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wavelength :</span></dt><dd>665.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.30 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2177, 2926) </td>\n",
+       "                        <td> (512, 512) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 30 chunks in 40 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"62\" x2=\"120\" y2=\"62\" />\n",
+       "  <line x1=\"0\" y1=\"83\" x2=\"120\" y2=\"83\" />\n",
+       "  <line x1=\"0\" y1=\"89\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"89\" />\n",
+       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"89\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"89\" />\n",
+       "  <line x1=\"83\" y1=\"0\" x2=\"83\" y2=\"89\" />\n",
+       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"89\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"89\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,89.28229665071771 0.0,89.28229665071771\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"109.282297\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2926</text>\n",
+       "  <text x=\"140.000000\" y=\"44.641148\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,44.641148)\">2177</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-79281599-a76e-4434-8833-af92c5588636' class='xr-section-summary-in' type='checkbox'  ><label for='section-79281599-a76e-4434-8833-af92c5588636' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-63727b58-94c3-444c-99b8-422809339035' class='xr-index-data-in' type='checkbox'/><label for='index-63727b58-94c3-444c-99b8-422809339035' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([         12.694301, 12.696800999999999,          12.699301,\n",
+       "                12.701801,          12.704301, 12.706800999999999,\n",
+       "                12.709301,          12.711801, 12.714300999999999,\n",
+       "                12.716801,\n",
+       "       ...\n",
+       "                19.984301,          19.986801, 19.989300999999998,\n",
+       "                19.991801,          19.994301, 19.996800999999998,\n",
+       "                19.999301,          20.001801, 20.004300999999998,\n",
+       "                20.006801],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2926))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-ccc11c9d-23ac-4e45-99d4-46a7849a9769' class='xr-index-data-in' type='checkbox'/><label for='index-ccc11c9d-23ac-4e45-99d4-46a7849a9769' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([          60.64018,           60.63768,           60.63518,\n",
+       "                 60.63268,           60.63018,           60.62768,\n",
+       "                 60.62518,           60.62268,           60.62018,\n",
+       "                 60.61768,\n",
+       "       ...\n",
+       "                 55.22268,           55.22018, 55.217679999999994,\n",
+       "                 55.21518,           55.21268, 55.210179999999994,\n",
+       "       55.207679999999996,           55.20518, 55.202679999999994,\n",
+       "       55.200179999999996],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2177))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-31b6d41e-749a-443f-8708-b3fdd3d13f38' class='xr-section-summary-in' type='checkbox'  checked><label for='section-31b6d41e-749a-443f-8708-b3fdd3d13f38' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>product_type :</span></dt><dd>C2RCC_OLCI</dd><dt><span>start_date :</span></dt><dd>04-JUL-2018 09:21:55.677316</dd><dt><span>stop_date :</span></dt><dd>04-JUL-2018 09:23:18.811790</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 102MB\n",
+       "Dimensions:        (lon: 2926, lat: 2177)\n",
+       "Coordinates:\n",
+       "    spatial_ref    int64 8B 0\n",
+       "  * lon            (lon) float64 23kB 12.69 12.7 12.7 12.7 ... 20.0 20.0 20.01\n",
+       "  * lat            (lat) float64 17kB 60.64 60.64 60.64 ... 55.21 55.2 55.2\n",
+       "Data variables:\n",
+       "    quality_flags  (lat, lon) uint32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_3         (lat, lon) float32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_6         (lat, lon) float32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "    rtoa_8         (lat, lon) float32 25MB dask.array<chunksize=(512, 512), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:   CF-1.4\n",
+       "    product_type:  C2RCC_OLCI\n",
+       "    start_date:    04-JUL-2018 09:21:55.677316\n",
+       "    stop_date:     04-JUL-2018 09:23:18.811790"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "target_ds_bilin = rectify_dataset(source_ds, interp_methods=\"bilinear\")\n",
+    "target_ds_bilin"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 3.04 s, sys: 177 ms, total: 3.22 s\n",
+      "Wall time: 1.48 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x760b084547d0>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "target_ds_bilin.rtoa_8.plot(cmap=\"gray\", vmax=0.2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, we visualize the difference between bilinear and nearest-neighbor interpolation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x760b10212850>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(target_ds_bilin.rtoa_8 - target_ds.rtoa_8).plot(vmin=-0.02, vmax=+0.02, cmap=\"RdBu\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/examples/resample_in_space_large_example_reproject_dataset.ipynb b/docs/examples/resample_in_space_large_example_reproject_dataset.ipynb
new file mode 100644
index 0000000..b8ce13e
--- /dev/null
+++ b/docs/examples/resample_in_space_large_example_reproject_dataset.ipynb
@@ -0,0 +1,4930 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "62866d66-22db-4f13-b585-3310df862833",
+   "metadata": {},
+   "source": [
+    "# Reproject the ESA-CCI land cover map for Europe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5fc41747-c179-4ba0-9388-032eacc870ad",
+   "metadata": {
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from xcube.core.store import new_data_store\n",
+    "from xcube_resampling.spatial import resample_in_space\n",
+    "from xcube_resampling.gridmapping import GridMapping\n",
+    "from datetime import datetime\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pyproj\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c252bd84-caf8-429f-8982-2fa904f21c5e",
+   "metadata": {},
+   "source": [
+    "We use the ESA CCI Land Cover map available from the [DeepESDL](https://www.earthsystemdatalab.net/) public S3 bucket. In the following cell, we access the multi-resolution dataset `\"LC-1x2025x2025-2.0.0.levels\"` and select the base level, which corresponds to the original spatial resolution of approximately 300 meters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1a18fbe6-9aac-4c8b-8c78-701ea899fbf7",
+   "metadata": {
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 226 ms, sys: 33.7 ms, total: 260 ms\n",
+      "Wall time: 1.01 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3TB\n",
+       "Dimensions:              (time: 31, lat: 64800, lon: 129600, bounds: 2)\n",
+       "Coordinates:\n",
+       "  * lat                  (lat) float64 518kB 90.0 90.0 89.99 ... -90.0 -90.0\n",
+       "  * lon                  (lon) float64 1MB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time                 (time) datetime64[ns] 248B 1992-01-01 ... 2022-01-01\n",
+       "Dimensions without coordinates: bounds\n",
+       "Data variables:\n",
+       "    change_count         (time, lat, lon) uint8 260GB dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;\n",
+       "    crs                  int32 4B ...\n",
+       "    current_pixel_state  (time, lat, lon) float32 1TB dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;\n",
+       "    lat_bounds           (lat, bounds) float64 1MB dask.array&lt;chunksize=(2025, 2), meta=np.ndarray&gt;\n",
+       "    lccs_class           (time, lat, lon) uint8 260GB dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;\n",
+       "    lon_bounds           (lon, bounds) float64 2MB dask.array&lt;chunksize=(2025, 2), meta=np.ndarray&gt;\n",
+       "    observation_count    (time, lat, lon) uint16 521GB dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;\n",
+       "    processed_flag       (time, lat, lon) float32 1TB dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;\n",
+       "    time_bounds          (time, bounds) datetime64[ns] 496B dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6d124df7-26d1-425b-b42f-dd60e5eb146d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6d124df7-26d1-425b-b42f-dd60e5eb146d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 31</li><li><span class='xr-has-index'>lat</span>: 64800</li><li><span class='xr-has-index'>lon</span>: 129600</li><li><span>bounds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-451a6f84-e693-4270-8978-37e2fec15e01' class='xr-section-summary-in' type='checkbox'  checked><label for='section-451a6f84-e693-4270-8978-37e2fec15e01' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 90.0 89.99 ... -90.0 -90.0</div><input id='attrs-bbe28e88-e810-4040-8928-7aab0a0978d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbe28e88-e810-4040-8928-7aab0a0978d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9d7b55b-a320-47d6-993f-c83bcd1df8a5' class='xr-var-data-in' type='checkbox'><label for='data-a9d7b55b-a320-47d6-993f-c83bcd1df8a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bounds</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([ 89.998611,  89.995833,  89.993056, ..., -89.993056, -89.995833,\n",
+       "       -89.998611], shape=(64800,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-7ede5516-53df-4a9a-ade2-63443a3ebbda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ede5516-53df-4a9a-ade2-63443a3ebbda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7295d218-6735-4a18-8738-e4f57b47be7e' class='xr-var-data-in' type='checkbox'><label for='data-7295d218-6735-4a18-8738-e4f57b47be7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bounds</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([-179.998611, -179.995833, -179.993056, ...,  179.993056,  179.995833,\n",
+       "        179.998611], shape=(129600,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1992-01-01 ... 2022-01-01</div><input id='attrs-cc25ca2e-8d0b-41ac-836c-d3300a060d6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc25ca2e-8d0b-41ac-836c-d3300a060d6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7236d3e9-fb5b-4712-8059-776defffb785' class='xr-var-data-in' type='checkbox'><label for='data-7236d3e9-fb5b-4712-8059-776defffb785' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1992-01-01T00:00:00.000000000&#x27;, &#x27;1993-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1994-01-01T00:00:00.000000000&#x27;, &#x27;1995-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1996-01-01T00:00:00.000000000&#x27;, &#x27;1997-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1998-01-01T00:00:00.000000000&#x27;, &#x27;1999-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2001-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2002-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2004-01-01T00:00:00.000000000&#x27;, &#x27;2005-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2006-01-01T00:00:00.000000000&#x27;, &#x27;2007-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2008-01-01T00:00:00.000000000&#x27;, &#x27;2009-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2010-01-01T00:00:00.000000000&#x27;, &#x27;2011-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2012-01-01T00:00:00.000000000&#x27;, &#x27;2013-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2014-01-01T00:00:00.000000000&#x27;, &#x27;2015-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2016-01-01T00:00:00.000000000&#x27;, &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2018-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-736fabc5-c6a0-4a87-8e84-cab43eb1b1cb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-736fabc5-c6a0-4a87-8e84-cab43eb1b1cb' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>change_count</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;</div><input id='attrs-435d466b-7fe9-41bc-a20b-ec3f03302dce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-435d466b-7fe9-41bc-a20b-ec3f03302dce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cdfb3cc-08bc-4dc7-a6b4-7c0bb822888c' class='xr-var-data-in' type='checkbox'><label for='data-9cdfb3cc-08bc-4dc7-a6b4-7c0bb822888c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>number of class changes</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 242.46 GiB </td>\n",
+       "                        <td> 3.91 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (31, 64800, 129600) </td>\n",
+       "                        <td> (1, 2025, 2025) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 63488 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"1\" x2=\"24\" y2=\"16\" />\n",
+       "  <line x1=\"10\" y1=\"5\" x2=\"24\" y2=\"20\" />\n",
+       "  <line x1=\"10\" y1=\"9\" x2=\"24\" y2=\"24\" />\n",
+       "  <line x1=\"10\" y1=\"11\" x2=\"24\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"15\" x2=\"24\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"18\" x2=\"24\" y2=\"33\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"24\" y2=\"35\" />\n",
+       "  <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"28\" x2=\"24\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"24\" y2=\"44\" />\n",
+       "  <line x1=\"10\" y1=\"33\" x2=\"24\" y2=\"48\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"24\" y2=\"52\" />\n",
+       "  <line x1=\"10\" y1=\"39\" x2=\"24\" y2=\"54\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"46\" x2=\"24\" y2=\"61\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"56\" x2=\"24\" y2=\"71\" />\n",
+       "  <line x1=\"10\" y1=\"60\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"62\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"63\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"64\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"65\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"67\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"68\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"69\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"71\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"72\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,74.9485979497544 10.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"15\" y1=\"0\" x2=\"30\" y2=\"14\" />\n",
+       "  <line x1=\"21\" y1=\"0\" x2=\"36\" y2=\"14\" />\n",
+       "  <line x1=\"28\" y1=\"0\" x2=\"43\" y2=\"14\" />\n",
+       "  <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
+       "  <line x1=\"40\" y1=\"0\" x2=\"54\" y2=\"14\" />\n",
+       "  <line x1=\"47\" y1=\"0\" x2=\"62\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"73\" y2=\"14\" />\n",
+       "  <line x1=\"66\" y1=\"0\" x2=\"81\" y2=\"14\" />\n",
+       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
+       "  <line x1=\"79\" y1=\"0\" x2=\"94\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
+       "  <line x1=\"90\" y1=\"0\" x2=\"105\" y2=\"14\" />\n",
+       "  <line x1=\"98\" y1=\"0\" x2=\"113\" y2=\"14\" />\n",
+       "  <line x1=\"103\" y1=\"0\" x2=\"118\" y2=\"14\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
+       "  <line x1=\"116\" y1=\"0\" x2=\"131\" y2=\"14\" />\n",
+       "  <line x1=\"122\" y1=\"0\" x2=\"137\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"16\" x2=\"144\" y2=\"16\" />\n",
+       "  <line x1=\"24\" y1=\"20\" x2=\"144\" y2=\"20\" />\n",
+       "  <line x1=\"24\" y1=\"24\" x2=\"144\" y2=\"24\" />\n",
+       "  <line x1=\"24\" y1=\"26\" x2=\"144\" y2=\"26\" />\n",
+       "  <line x1=\"24\" y1=\"29\" x2=\"144\" y2=\"29\" />\n",
+       "  <line x1=\"24\" y1=\"33\" x2=\"144\" y2=\"33\" />\n",
+       "  <line x1=\"24\" y1=\"35\" x2=\"144\" y2=\"35\" />\n",
+       "  <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
+       "  <line x1=\"24\" y1=\"43\" x2=\"144\" y2=\"43\" />\n",
+       "  <line x1=\"24\" y1=\"44\" x2=\"144\" y2=\"44\" />\n",
+       "  <line x1=\"24\" y1=\"48\" x2=\"144\" y2=\"48\" />\n",
+       "  <line x1=\"24\" y1=\"52\" x2=\"144\" y2=\"52\" />\n",
+       "  <line x1=\"24\" y1=\"54\" x2=\"144\" y2=\"54\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"144\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"61\" x2=\"144\" y2=\"61\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" />\n",
+       "  <line x1=\"24\" y1=\"71\" x2=\"144\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"74\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"14\" x2=\"30\" y2=\"74\" />\n",
+       "  <line x1=\"36\" y1=\"14\" x2=\"36\" y2=\"74\" />\n",
+       "  <line x1=\"43\" y1=\"14\" x2=\"43\" y2=\"74\" />\n",
+       "  <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"74\" />\n",
+       "  <line x1=\"54\" y1=\"14\" x2=\"54\" y2=\"74\" />\n",
+       "  <line x1=\"62\" y1=\"14\" x2=\"62\" y2=\"74\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"74\" />\n",
+       "  <line x1=\"73\" y1=\"14\" x2=\"73\" y2=\"74\" />\n",
+       "  <line x1=\"81\" y1=\"14\" x2=\"81\" y2=\"74\" />\n",
+       "  <line x1=\"86\" y1=\"14\" x2=\"86\" y2=\"74\" />\n",
+       "  <line x1=\"94\" y1=\"14\" x2=\"94\" y2=\"74\" />\n",
+       "  <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"74\" />\n",
+       "  <line x1=\"105\" y1=\"14\" x2=\"105\" y2=\"74\" />\n",
+       "  <line x1=\"113\" y1=\"14\" x2=\"113\" y2=\"74\" />\n",
+       "  <line x1=\"118\" y1=\"14\" x2=\"118\" y2=\"74\" />\n",
+       "  <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"74\" />\n",
+       "  <line x1=\"131\" y1=\"14\" x2=\"131\" y2=\"74\" />\n",
+       "  <line x1=\"137\" y1=\"14\" x2=\"137\" y2=\"74\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,74.9485979497544 24.9485979497544,74.9485979497544\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"94.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >129600</text>\n",
+       "  <text x=\"164.948598\" y=\"44.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,44.948598)\">64800</text>\n",
+       "  <text x=\"7.474299\" y=\"87.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,87.474299)\">31</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-babd5dbf-464f-4e89-8175-c49a3a3d9219' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-babd5dbf-464f-4e89-8175-c49a3a3d9219' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68458e84-4c33-4e49-b40c-983e78a24be3' class='xr-var-data-in' type='checkbox'><label for='data-68458e84-4c33-4e49-b40c-983e78a24be3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>i2m :</span></dt><dd>0.002777777777778,0.0,0.0,-0.002777777777778,-180.0,90.0</dd><dt><span>wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;, \n",
+       "  DATUM[&quot;World Geodetic System 1984&quot;, \n",
+       "    SPHEROID[&quot;WGS 84&quot;, 6378137.0, 298.257223563, AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]], \n",
+       "    AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]], \n",
+       "  PRIMEM[&quot;Greenwich&quot;, 0.0, AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]], \n",
+       "  UNIT[&quot;degree&quot;, 0.017453292519943295], \n",
+       "  AXIS[&quot;Geodetic longitude&quot;, EAST], \n",
+       "  AXIS[&quot;Geodetic latitude&quot;, NORTH], \n",
+       "  AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>current_pixel_state</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;</div><input id='attrs-64ba9182-35fb-4a43-84f9-52ae62909147' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64ba9182-35fb-4a43-84f9-52ae62909147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed0f61a7-b393-44cf-8868-2c7ff00d7954' class='xr-var-data-in' type='checkbox'><label for='data-ed0f61a7-b393-44cf-8868-2c7ff00d7954' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_meanings :</span></dt><dd>invalid clear_land clear_water clear_snow_ice cloud cloud_shadow</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3, 4, 5]</dd><dt><span>long_name :</span></dt><dd>LC pixel type mask</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs status_flag</dd><dt><span>valid_max :</span></dt><dd>5</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.95 TiB </td>\n",
+       "                        <td> 15.64 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (31, 64800, 129600) </td>\n",
+       "                        <td> (1, 2025, 2025) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 63488 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"1\" x2=\"24\" y2=\"16\" />\n",
+       "  <line x1=\"10\" y1=\"5\" x2=\"24\" y2=\"20\" />\n",
+       "  <line x1=\"10\" y1=\"9\" x2=\"24\" y2=\"24\" />\n",
+       "  <line x1=\"10\" y1=\"11\" x2=\"24\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"15\" x2=\"24\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"18\" x2=\"24\" y2=\"33\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"24\" y2=\"35\" />\n",
+       "  <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"28\" x2=\"24\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"24\" y2=\"44\" />\n",
+       "  <line x1=\"10\" y1=\"33\" x2=\"24\" y2=\"48\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"24\" y2=\"52\" />\n",
+       "  <line x1=\"10\" y1=\"39\" x2=\"24\" y2=\"54\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"46\" x2=\"24\" y2=\"61\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"56\" x2=\"24\" y2=\"71\" />\n",
+       "  <line x1=\"10\" y1=\"60\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"62\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"63\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"64\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"65\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"67\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"68\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"69\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"71\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"72\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,74.9485979497544 10.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"15\" y1=\"0\" x2=\"30\" y2=\"14\" />\n",
+       "  <line x1=\"21\" y1=\"0\" x2=\"36\" y2=\"14\" />\n",
+       "  <line x1=\"28\" y1=\"0\" x2=\"43\" y2=\"14\" />\n",
+       "  <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
+       "  <line x1=\"40\" y1=\"0\" x2=\"54\" y2=\"14\" />\n",
+       "  <line x1=\"47\" y1=\"0\" x2=\"62\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"73\" y2=\"14\" />\n",
+       "  <line x1=\"66\" y1=\"0\" x2=\"81\" y2=\"14\" />\n",
+       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
+       "  <line x1=\"79\" y1=\"0\" x2=\"94\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
+       "  <line x1=\"90\" y1=\"0\" x2=\"105\" y2=\"14\" />\n",
+       "  <line x1=\"98\" y1=\"0\" x2=\"113\" y2=\"14\" />\n",
+       "  <line x1=\"103\" y1=\"0\" x2=\"118\" y2=\"14\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
+       "  <line x1=\"116\" y1=\"0\" x2=\"131\" y2=\"14\" />\n",
+       "  <line x1=\"122\" y1=\"0\" x2=\"137\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"16\" x2=\"144\" y2=\"16\" />\n",
+       "  <line x1=\"24\" y1=\"20\" x2=\"144\" y2=\"20\" />\n",
+       "  <line x1=\"24\" y1=\"24\" x2=\"144\" y2=\"24\" />\n",
+       "  <line x1=\"24\" y1=\"26\" x2=\"144\" y2=\"26\" />\n",
+       "  <line x1=\"24\" y1=\"29\" x2=\"144\" y2=\"29\" />\n",
+       "  <line x1=\"24\" y1=\"33\" x2=\"144\" y2=\"33\" />\n",
+       "  <line x1=\"24\" y1=\"35\" x2=\"144\" y2=\"35\" />\n",
+       "  <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
+       "  <line x1=\"24\" y1=\"43\" x2=\"144\" y2=\"43\" />\n",
+       "  <line x1=\"24\" y1=\"44\" x2=\"144\" y2=\"44\" />\n",
+       "  <line x1=\"24\" y1=\"48\" x2=\"144\" y2=\"48\" />\n",
+       "  <line x1=\"24\" y1=\"52\" x2=\"144\" y2=\"52\" />\n",
+       "  <line x1=\"24\" y1=\"54\" x2=\"144\" y2=\"54\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"144\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"61\" x2=\"144\" y2=\"61\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" />\n",
+       "  <line x1=\"24\" y1=\"71\" x2=\"144\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"74\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"14\" x2=\"30\" y2=\"74\" />\n",
+       "  <line x1=\"36\" y1=\"14\" x2=\"36\" y2=\"74\" />\n",
+       "  <line x1=\"43\" y1=\"14\" x2=\"43\" y2=\"74\" />\n",
+       "  <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"74\" />\n",
+       "  <line x1=\"54\" y1=\"14\" x2=\"54\" y2=\"74\" />\n",
+       "  <line x1=\"62\" y1=\"14\" x2=\"62\" y2=\"74\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"74\" />\n",
+       "  <line x1=\"73\" y1=\"14\" x2=\"73\" y2=\"74\" />\n",
+       "  <line x1=\"81\" y1=\"14\" x2=\"81\" y2=\"74\" />\n",
+       "  <line x1=\"86\" y1=\"14\" x2=\"86\" y2=\"74\" />\n",
+       "  <line x1=\"94\" y1=\"14\" x2=\"94\" y2=\"74\" />\n",
+       "  <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"74\" />\n",
+       "  <line x1=\"105\" y1=\"14\" x2=\"105\" y2=\"74\" />\n",
+       "  <line x1=\"113\" y1=\"14\" x2=\"113\" y2=\"74\" />\n",
+       "  <line x1=\"118\" y1=\"14\" x2=\"118\" y2=\"74\" />\n",
+       "  <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"74\" />\n",
+       "  <line x1=\"131\" y1=\"14\" x2=\"131\" y2=\"74\" />\n",
+       "  <line x1=\"137\" y1=\"14\" x2=\"137\" y2=\"74\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,74.9485979497544 24.9485979497544,74.9485979497544\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"94.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >129600</text>\n",
+       "  <text x=\"164.948598\" y=\"44.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,44.948598)\">64800</text>\n",
+       "  <text x=\"7.474299\" y=\"87.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,87.474299)\">31</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bounds</span></div><div class='xr-var-dims'>(lat, bounds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2025, 2), meta=np.ndarray&gt;</div><input id='attrs-f96a4700-c640-40fa-9ca2-b945d6f29ad0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f96a4700-c640-40fa-9ca2-b945d6f29ad0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48a35a2e-f9f2-4c30-9137-115e4a2d2315' class='xr-var-data-in' type='checkbox'><label for='data-48a35a2e-f9f2-4c30-9137-115e4a2d2315' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.99 MiB </td>\n",
+       "                        <td> 31.64 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (64800, 2) </td>\n",
+       "                        <td> (2025, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 32 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"25\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"25\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"18\" x2=\"25\" y2=\"18\" />\n",
+       "  <line x1=\"0\" y1=\"22\" x2=\"25\" y2=\"22\" />\n",
+       "  <line x1=\"0\" y1=\"30\" x2=\"25\" y2=\"30\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"25\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"48\" x2=\"25\" y2=\"48\" />\n",
+       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"25\" y2=\"60\" />\n",
+       "  <line x1=\"0\" y1=\"67\" x2=\"25\" y2=\"67\" />\n",
+       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
+       "  <line x1=\"0\" y1=\"78\" x2=\"25\" y2=\"78\" />\n",
+       "  <line x1=\"0\" y1=\"86\" x2=\"25\" y2=\"86\" />\n",
+       "  <line x1=\"0\" y1=\"93\" x2=\"25\" y2=\"93\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"25\" y2=\"97\" />\n",
+       "  <line x1=\"0\" y1=\"105\" x2=\"25\" y2=\"105\" />\n",
+       "  <line x1=\"0\" y1=\"112\" x2=\"25\" y2=\"112\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">64800</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lccs_class</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;</div><input id='attrs-30841bae-9941-416b-be28-cbb4b5ffd62b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30841bae-9941-416b-be28-cbb4b5ffd62b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09e95b45-baf1-4bd0-a022-9bf79b882abe' class='xr-var-data-in' type='checkbox'><label for='data-09e95b45-baf1-4bd0-a022-9bf79b882abe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ancillary_variables :</span></dt><dd>processed_flag current_pixel_state observation_count change_count</dd><dt><span>flag_colors :</span></dt><dd>#ffff64 #ffff64 #ffff00 #aaf0f0 #dcf064 #c8c864 #006400 #00a000 #00a000 #aac800 #003c00 #003c00 #005000 #285000 #285000 #286400 #788200 #8ca000 #be9600 #966400 #966400 #966400 #ffb432 #ffdcd2 #ffebaf #ffc864 #ffd278 #ffebaf #00785a #009678 #00dc82 #c31400 #fff5d7 #dcdcdc #fff5d7 #0046c8 #ffffff</dd><dt><span>flag_meanings :</span></dt><dd>no_data cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban bare_areas bare_areas_consolidated bare_areas_unconsolidated water snow_and_ice</dd><dt><span>flag_values :</span></dt><dd>[0, 10, 11, 12, 20, 30, 40, 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100, 110, 120, 121, 122, 130, 140, 150, 151, 152, 153, 160, 170, 180, 190, 200, 201, 202, 210, 220]</dd><dt><span>long_name :</span></dt><dd>Land cover class defined in LCCS</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs</dd><dt><span>valid_max :</span></dt><dd>220</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 242.46 GiB </td>\n",
+       "                        <td> 3.91 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (31, 64800, 129600) </td>\n",
+       "                        <td> (1, 2025, 2025) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 63488 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"1\" x2=\"24\" y2=\"16\" />\n",
+       "  <line x1=\"10\" y1=\"5\" x2=\"24\" y2=\"20\" />\n",
+       "  <line x1=\"10\" y1=\"9\" x2=\"24\" y2=\"24\" />\n",
+       "  <line x1=\"10\" y1=\"11\" x2=\"24\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"15\" x2=\"24\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"18\" x2=\"24\" y2=\"33\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"24\" y2=\"35\" />\n",
+       "  <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"28\" x2=\"24\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"24\" y2=\"44\" />\n",
+       "  <line x1=\"10\" y1=\"33\" x2=\"24\" y2=\"48\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"24\" y2=\"52\" />\n",
+       "  <line x1=\"10\" y1=\"39\" x2=\"24\" y2=\"54\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"46\" x2=\"24\" y2=\"61\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"56\" x2=\"24\" y2=\"71\" />\n",
+       "  <line x1=\"10\" y1=\"60\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"62\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"63\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"64\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"65\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"67\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"68\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"69\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"71\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"72\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,74.9485979497544 10.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"15\" y1=\"0\" x2=\"30\" y2=\"14\" />\n",
+       "  <line x1=\"21\" y1=\"0\" x2=\"36\" y2=\"14\" />\n",
+       "  <line x1=\"28\" y1=\"0\" x2=\"43\" y2=\"14\" />\n",
+       "  <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
+       "  <line x1=\"40\" y1=\"0\" x2=\"54\" y2=\"14\" />\n",
+       "  <line x1=\"47\" y1=\"0\" x2=\"62\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"73\" y2=\"14\" />\n",
+       "  <line x1=\"66\" y1=\"0\" x2=\"81\" y2=\"14\" />\n",
+       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
+       "  <line x1=\"79\" y1=\"0\" x2=\"94\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
+       "  <line x1=\"90\" y1=\"0\" x2=\"105\" y2=\"14\" />\n",
+       "  <line x1=\"98\" y1=\"0\" x2=\"113\" y2=\"14\" />\n",
+       "  <line x1=\"103\" y1=\"0\" x2=\"118\" y2=\"14\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
+       "  <line x1=\"116\" y1=\"0\" x2=\"131\" y2=\"14\" />\n",
+       "  <line x1=\"122\" y1=\"0\" x2=\"137\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"16\" x2=\"144\" y2=\"16\" />\n",
+       "  <line x1=\"24\" y1=\"20\" x2=\"144\" y2=\"20\" />\n",
+       "  <line x1=\"24\" y1=\"24\" x2=\"144\" y2=\"24\" />\n",
+       "  <line x1=\"24\" y1=\"26\" x2=\"144\" y2=\"26\" />\n",
+       "  <line x1=\"24\" y1=\"29\" x2=\"144\" y2=\"29\" />\n",
+       "  <line x1=\"24\" y1=\"33\" x2=\"144\" y2=\"33\" />\n",
+       "  <line x1=\"24\" y1=\"35\" x2=\"144\" y2=\"35\" />\n",
+       "  <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
+       "  <line x1=\"24\" y1=\"43\" x2=\"144\" y2=\"43\" />\n",
+       "  <line x1=\"24\" y1=\"44\" x2=\"144\" y2=\"44\" />\n",
+       "  <line x1=\"24\" y1=\"48\" x2=\"144\" y2=\"48\" />\n",
+       "  <line x1=\"24\" y1=\"52\" x2=\"144\" y2=\"52\" />\n",
+       "  <line x1=\"24\" y1=\"54\" x2=\"144\" y2=\"54\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"144\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"61\" x2=\"144\" y2=\"61\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" />\n",
+       "  <line x1=\"24\" y1=\"71\" x2=\"144\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"74\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"14\" x2=\"30\" y2=\"74\" />\n",
+       "  <line x1=\"36\" y1=\"14\" x2=\"36\" y2=\"74\" />\n",
+       "  <line x1=\"43\" y1=\"14\" x2=\"43\" y2=\"74\" />\n",
+       "  <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"74\" />\n",
+       "  <line x1=\"54\" y1=\"14\" x2=\"54\" y2=\"74\" />\n",
+       "  <line x1=\"62\" y1=\"14\" x2=\"62\" y2=\"74\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"74\" />\n",
+       "  <line x1=\"73\" y1=\"14\" x2=\"73\" y2=\"74\" />\n",
+       "  <line x1=\"81\" y1=\"14\" x2=\"81\" y2=\"74\" />\n",
+       "  <line x1=\"86\" y1=\"14\" x2=\"86\" y2=\"74\" />\n",
+       "  <line x1=\"94\" y1=\"14\" x2=\"94\" y2=\"74\" />\n",
+       "  <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"74\" />\n",
+       "  <line x1=\"105\" y1=\"14\" x2=\"105\" y2=\"74\" />\n",
+       "  <line x1=\"113\" y1=\"14\" x2=\"113\" y2=\"74\" />\n",
+       "  <line x1=\"118\" y1=\"14\" x2=\"118\" y2=\"74\" />\n",
+       "  <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"74\" />\n",
+       "  <line x1=\"131\" y1=\"14\" x2=\"131\" y2=\"74\" />\n",
+       "  <line x1=\"137\" y1=\"14\" x2=\"137\" y2=\"74\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,74.9485979497544 24.9485979497544,74.9485979497544\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"94.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >129600</text>\n",
+       "  <text x=\"164.948598\" y=\"44.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,44.948598)\">64800</text>\n",
+       "  <text x=\"7.474299\" y=\"87.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,87.474299)\">31</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bounds</span></div><div class='xr-var-dims'>(lon, bounds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2025, 2), meta=np.ndarray&gt;</div><input id='attrs-4d0f19cd-0458-484d-a724-65c7f9611bdd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d0f19cd-0458-484d-a724-65c7f9611bdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b39495bd-6a76-4dad-ba07-8ac4abf0cc94' class='xr-var-data-in' type='checkbox'><label for='data-b39495bd-6a76-4dad-ba07-8ac4abf0cc94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.98 MiB </td>\n",
+       "                        <td> 31.64 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (129600, 2) </td>\n",
+       "                        <td> (2025, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 64 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"25\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"25\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"18\" x2=\"25\" y2=\"18\" />\n",
+       "  <line x1=\"0\" y1=\"24\" x2=\"25\" y2=\"24\" />\n",
+       "  <line x1=\"0\" y1=\"30\" x2=\"25\" y2=\"30\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
+       "  <line x1=\"0\" y1=\"43\" x2=\"25\" y2=\"43\" />\n",
+       "  <line x1=\"0\" y1=\"48\" x2=\"25\" y2=\"48\" />\n",
+       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
+       "  <line x1=\"0\" y1=\"61\" x2=\"25\" y2=\"61\" />\n",
+       "  <line x1=\"0\" y1=\"69\" x2=\"25\" y2=\"69\" />\n",
+       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
+       "  <line x1=\"0\" y1=\"80\" x2=\"25\" y2=\"80\" />\n",
+       "  <line x1=\"0\" y1=\"88\" x2=\"25\" y2=\"88\" />\n",
+       "  <line x1=\"0\" y1=\"93\" x2=\"25\" y2=\"93\" />\n",
+       "  <line x1=\"0\" y1=\"99\" x2=\"25\" y2=\"99\" />\n",
+       "  <line x1=\"0\" y1=\"106\" x2=\"25\" y2=\"106\" />\n",
+       "  <line x1=\"0\" y1=\"112\" x2=\"25\" y2=\"112\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">129600</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>observation_count</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;</div><input id='attrs-a35de2da-8308-4c51-929d-12b4b7844084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a35de2da-8308-4c51-929d-12b4b7844084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f96d657-3e6f-42d4-8835-560fddac8f54' class='xr-var-data-in' type='checkbox'><label for='data-2f96d657-3e6f-42d4-8835-560fddac8f54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>number of valid observations</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs number_of_observations</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 484.92 GiB </td>\n",
+       "                        <td> 7.82 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (31, 64800, 129600) </td>\n",
+       "                        <td> (1, 2025, 2025) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 63488 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"1\" x2=\"24\" y2=\"16\" />\n",
+       "  <line x1=\"10\" y1=\"5\" x2=\"24\" y2=\"20\" />\n",
+       "  <line x1=\"10\" y1=\"9\" x2=\"24\" y2=\"24\" />\n",
+       "  <line x1=\"10\" y1=\"11\" x2=\"24\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"15\" x2=\"24\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"18\" x2=\"24\" y2=\"33\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"24\" y2=\"35\" />\n",
+       "  <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"28\" x2=\"24\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"24\" y2=\"44\" />\n",
+       "  <line x1=\"10\" y1=\"33\" x2=\"24\" y2=\"48\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"24\" y2=\"52\" />\n",
+       "  <line x1=\"10\" y1=\"39\" x2=\"24\" y2=\"54\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"46\" x2=\"24\" y2=\"61\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"56\" x2=\"24\" y2=\"71\" />\n",
+       "  <line x1=\"10\" y1=\"60\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"62\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"63\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"64\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"65\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"67\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"68\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"69\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"71\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"72\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,74.9485979497544 10.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"15\" y1=\"0\" x2=\"30\" y2=\"14\" />\n",
+       "  <line x1=\"21\" y1=\"0\" x2=\"36\" y2=\"14\" />\n",
+       "  <line x1=\"28\" y1=\"0\" x2=\"43\" y2=\"14\" />\n",
+       "  <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
+       "  <line x1=\"40\" y1=\"0\" x2=\"54\" y2=\"14\" />\n",
+       "  <line x1=\"47\" y1=\"0\" x2=\"62\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"73\" y2=\"14\" />\n",
+       "  <line x1=\"66\" y1=\"0\" x2=\"81\" y2=\"14\" />\n",
+       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
+       "  <line x1=\"79\" y1=\"0\" x2=\"94\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
+       "  <line x1=\"90\" y1=\"0\" x2=\"105\" y2=\"14\" />\n",
+       "  <line x1=\"98\" y1=\"0\" x2=\"113\" y2=\"14\" />\n",
+       "  <line x1=\"103\" y1=\"0\" x2=\"118\" y2=\"14\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
+       "  <line x1=\"116\" y1=\"0\" x2=\"131\" y2=\"14\" />\n",
+       "  <line x1=\"122\" y1=\"0\" x2=\"137\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"16\" x2=\"144\" y2=\"16\" />\n",
+       "  <line x1=\"24\" y1=\"20\" x2=\"144\" y2=\"20\" />\n",
+       "  <line x1=\"24\" y1=\"24\" x2=\"144\" y2=\"24\" />\n",
+       "  <line x1=\"24\" y1=\"26\" x2=\"144\" y2=\"26\" />\n",
+       "  <line x1=\"24\" y1=\"29\" x2=\"144\" y2=\"29\" />\n",
+       "  <line x1=\"24\" y1=\"33\" x2=\"144\" y2=\"33\" />\n",
+       "  <line x1=\"24\" y1=\"35\" x2=\"144\" y2=\"35\" />\n",
+       "  <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
+       "  <line x1=\"24\" y1=\"43\" x2=\"144\" y2=\"43\" />\n",
+       "  <line x1=\"24\" y1=\"44\" x2=\"144\" y2=\"44\" />\n",
+       "  <line x1=\"24\" y1=\"48\" x2=\"144\" y2=\"48\" />\n",
+       "  <line x1=\"24\" y1=\"52\" x2=\"144\" y2=\"52\" />\n",
+       "  <line x1=\"24\" y1=\"54\" x2=\"144\" y2=\"54\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"144\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"61\" x2=\"144\" y2=\"61\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" />\n",
+       "  <line x1=\"24\" y1=\"71\" x2=\"144\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"74\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"14\" x2=\"30\" y2=\"74\" />\n",
+       "  <line x1=\"36\" y1=\"14\" x2=\"36\" y2=\"74\" />\n",
+       "  <line x1=\"43\" y1=\"14\" x2=\"43\" y2=\"74\" />\n",
+       "  <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"74\" />\n",
+       "  <line x1=\"54\" y1=\"14\" x2=\"54\" y2=\"74\" />\n",
+       "  <line x1=\"62\" y1=\"14\" x2=\"62\" y2=\"74\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"74\" />\n",
+       "  <line x1=\"73\" y1=\"14\" x2=\"73\" y2=\"74\" />\n",
+       "  <line x1=\"81\" y1=\"14\" x2=\"81\" y2=\"74\" />\n",
+       "  <line x1=\"86\" y1=\"14\" x2=\"86\" y2=\"74\" />\n",
+       "  <line x1=\"94\" y1=\"14\" x2=\"94\" y2=\"74\" />\n",
+       "  <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"74\" />\n",
+       "  <line x1=\"105\" y1=\"14\" x2=\"105\" y2=\"74\" />\n",
+       "  <line x1=\"113\" y1=\"14\" x2=\"113\" y2=\"74\" />\n",
+       "  <line x1=\"118\" y1=\"14\" x2=\"118\" y2=\"74\" />\n",
+       "  <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"74\" />\n",
+       "  <line x1=\"131\" y1=\"14\" x2=\"131\" y2=\"74\" />\n",
+       "  <line x1=\"137\" y1=\"14\" x2=\"137\" y2=\"74\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,74.9485979497544 24.9485979497544,74.9485979497544\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"94.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >129600</text>\n",
+       "  <text x=\"164.948598\" y=\"44.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,44.948598)\">64800</text>\n",
+       "  <text x=\"7.474299\" y=\"87.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,87.474299)\">31</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>processed_flag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;</div><input id='attrs-9f9111db-ecc5-485a-a018-6dad385fc67f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f9111db-ecc5-485a-a018-6dad385fc67f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e08324aa-dbe0-4df5-939c-4e8854f1fe0e' class='xr-var-data-in' type='checkbox'><label for='data-e08324aa-dbe0-4df5-939c-4e8854f1fe0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_meanings :</span></dt><dd>not_processed processed</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>long_name :</span></dt><dd>LC map processed area flag</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs status_flag</dd><dt><span>valid_max :</span></dt><dd>1</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.95 TiB </td>\n",
+       "                        <td> 15.64 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (31, 64800, 129600) </td>\n",
+       "                        <td> (1, 2025, 2025) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 63488 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"1\" x2=\"24\" y2=\"16\" />\n",
+       "  <line x1=\"10\" y1=\"5\" x2=\"24\" y2=\"20\" />\n",
+       "  <line x1=\"10\" y1=\"9\" x2=\"24\" y2=\"24\" />\n",
+       "  <line x1=\"10\" y1=\"11\" x2=\"24\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"15\" x2=\"24\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"18\" x2=\"24\" y2=\"33\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"24\" y2=\"35\" />\n",
+       "  <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"28\" x2=\"24\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"24\" y2=\"44\" />\n",
+       "  <line x1=\"10\" y1=\"33\" x2=\"24\" y2=\"48\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"24\" y2=\"52\" />\n",
+       "  <line x1=\"10\" y1=\"39\" x2=\"24\" y2=\"54\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"46\" x2=\"24\" y2=\"61\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"56\" x2=\"24\" y2=\"71\" />\n",
+       "  <line x1=\"10\" y1=\"60\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"11\" y2=\"61\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"62\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"63\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"64\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"65\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"16\" y2=\"66\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"67\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"68\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"69\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"70\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"71\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"72\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"73\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,74.9485979497544 10.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"11\" y1=\"1\" x2=\"131\" y2=\"1\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"16\" y1=\"6\" x2=\"136\" y2=\"6\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"20\" y1=\"10\" x2=\"140\" y2=\"10\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"15\" y1=\"0\" x2=\"30\" y2=\"14\" />\n",
+       "  <line x1=\"21\" y1=\"0\" x2=\"36\" y2=\"14\" />\n",
+       "  <line x1=\"28\" y1=\"0\" x2=\"43\" y2=\"14\" />\n",
+       "  <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
+       "  <line x1=\"40\" y1=\"0\" x2=\"54\" y2=\"14\" />\n",
+       "  <line x1=\"47\" y1=\"0\" x2=\"62\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"73\" y2=\"14\" />\n",
+       "  <line x1=\"66\" y1=\"0\" x2=\"81\" y2=\"14\" />\n",
+       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
+       "  <line x1=\"79\" y1=\"0\" x2=\"94\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
+       "  <line x1=\"90\" y1=\"0\" x2=\"105\" y2=\"14\" />\n",
+       "  <line x1=\"98\" y1=\"0\" x2=\"113\" y2=\"14\" />\n",
+       "  <line x1=\"103\" y1=\"0\" x2=\"118\" y2=\"14\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
+       "  <line x1=\"116\" y1=\"0\" x2=\"131\" y2=\"14\" />\n",
+       "  <line x1=\"122\" y1=\"0\" x2=\"137\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"16\" x2=\"144\" y2=\"16\" />\n",
+       "  <line x1=\"24\" y1=\"20\" x2=\"144\" y2=\"20\" />\n",
+       "  <line x1=\"24\" y1=\"24\" x2=\"144\" y2=\"24\" />\n",
+       "  <line x1=\"24\" y1=\"26\" x2=\"144\" y2=\"26\" />\n",
+       "  <line x1=\"24\" y1=\"29\" x2=\"144\" y2=\"29\" />\n",
+       "  <line x1=\"24\" y1=\"33\" x2=\"144\" y2=\"33\" />\n",
+       "  <line x1=\"24\" y1=\"35\" x2=\"144\" y2=\"35\" />\n",
+       "  <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
+       "  <line x1=\"24\" y1=\"43\" x2=\"144\" y2=\"43\" />\n",
+       "  <line x1=\"24\" y1=\"44\" x2=\"144\" y2=\"44\" />\n",
+       "  <line x1=\"24\" y1=\"48\" x2=\"144\" y2=\"48\" />\n",
+       "  <line x1=\"24\" y1=\"52\" x2=\"144\" y2=\"52\" />\n",
+       "  <line x1=\"24\" y1=\"54\" x2=\"144\" y2=\"54\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"144\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"61\" x2=\"144\" y2=\"61\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" />\n",
+       "  <line x1=\"24\" y1=\"71\" x2=\"144\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"74\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"14\" x2=\"30\" y2=\"74\" />\n",
+       "  <line x1=\"36\" y1=\"14\" x2=\"36\" y2=\"74\" />\n",
+       "  <line x1=\"43\" y1=\"14\" x2=\"43\" y2=\"74\" />\n",
+       "  <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"74\" />\n",
+       "  <line x1=\"54\" y1=\"14\" x2=\"54\" y2=\"74\" />\n",
+       "  <line x1=\"62\" y1=\"14\" x2=\"62\" y2=\"74\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"74\" />\n",
+       "  <line x1=\"73\" y1=\"14\" x2=\"73\" y2=\"74\" />\n",
+       "  <line x1=\"81\" y1=\"14\" x2=\"81\" y2=\"74\" />\n",
+       "  <line x1=\"86\" y1=\"14\" x2=\"86\" y2=\"74\" />\n",
+       "  <line x1=\"94\" y1=\"14\" x2=\"94\" y2=\"74\" />\n",
+       "  <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"74\" />\n",
+       "  <line x1=\"105\" y1=\"14\" x2=\"105\" y2=\"74\" />\n",
+       "  <line x1=\"113\" y1=\"14\" x2=\"113\" y2=\"74\" />\n",
+       "  <line x1=\"118\" y1=\"14\" x2=\"118\" y2=\"74\" />\n",
+       "  <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"74\" />\n",
+       "  <line x1=\"131\" y1=\"14\" x2=\"131\" y2=\"74\" />\n",
+       "  <line x1=\"137\" y1=\"14\" x2=\"137\" y2=\"74\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,74.9485979497544 24.9485979497544,74.9485979497544\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"94.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >129600</text>\n",
+       "  <text x=\"164.948598\" y=\"44.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,44.948598)\">64800</text>\n",
+       "  <text x=\"7.474299\" y=\"87.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,87.474299)\">31</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bounds</span></div><div class='xr-var-dims'>(time, bounds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-2cb560c9-927f-4bc0-b8ee-9a6b8c097808' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2cb560c9-927f-4bc0-b8ee-9a6b8c097808' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e14ce54d-f6f8-40c7-a294-9e300d9967c5' class='xr-var-data-in' type='checkbox'><label for='data-e14ce54d-f6f8-40c7-a294-9e300d9967c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 496 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (31, 2) </td>\n",
+       "                        <td> (1, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 31 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"86\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"36\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"36\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"36\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"36\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"36\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"30\" x2=\"36\" y2=\"30\" />\n",
+       "  <line x1=\"0\" y1=\"34\" x2=\"36\" y2=\"34\" />\n",
+       "  <line x1=\"0\" y1=\"42\" x2=\"36\" y2=\"42\" />\n",
+       "  <line x1=\"0\" y1=\"50\" x2=\"36\" y2=\"50\" />\n",
+       "  <line x1=\"0\" y1=\"54\" x2=\"36\" y2=\"54\" />\n",
+       "  <line x1=\"0\" y1=\"61\" x2=\"36\" y2=\"61\" />\n",
+       "  <line x1=\"0\" y1=\"65\" x2=\"36\" y2=\"65\" />\n",
+       "  <line x1=\"0\" y1=\"73\" x2=\"36\" y2=\"73\" />\n",
+       "  <line x1=\"0\" y1=\"81\" x2=\"36\" y2=\"81\" />\n",
+       "  <line x1=\"0\" y1=\"85\" x2=\"36\" y2=\"85\" />\n",
+       "  <line x1=\"0\" y1=\"92\" x2=\"36\" y2=\"92\" />\n",
+       "  <line x1=\"0\" y1=\"100\" x2=\"36\" y2=\"100\" />\n",
+       "  <line x1=\"0\" y1=\"104\" x2=\"36\" y2=\"104\" />\n",
+       "  <line x1=\"0\" y1=\"112\" x2=\"36\" y2=\"112\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"36\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"36\" y1=\"0\" x2=\"36\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 36.05090363626093,0.0 36.05090363626093,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"18.025452\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"56.050904\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,56.050904,60.000000)\">31</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-aea15cf0-68ba-4383-a4f7-534a2a7a5bde' class='xr-section-summary-in' type='checkbox'  ><label for='section-aea15cf0-68ba-4383-a4f7-534a2a7a5bde' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-13d9662d-3f33-434a-a1bb-da07542409e3' class='xr-index-data-in' type='checkbox'/><label for='index-13d9662d-3f33-434a-a1bb-da07542409e3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 89.99861111111113,  89.99583333333334,  89.99305555555557,\n",
+       "        89.99027777777778,  89.98750000000001,  89.98472222222222,\n",
+       "        89.98194444444445,  89.97916666666669,  89.97638888888889,\n",
+       "        89.97361111111113,\n",
+       "       ...\n",
+       "       -89.97361111111111, -89.97638888888889, -89.97916666666667,\n",
+       "       -89.98194444444445, -89.98472222222222,           -89.9875,\n",
+       "       -89.99027777777778, -89.99305555555556, -89.99583333333334,\n",
+       "       -89.99861111111112],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=64800))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-dbe8e525-7562-4c16-a208-4f2fe3cb277b' class='xr-index-data-in' type='checkbox'/><label for='index-dbe8e525-7562-4c16-a208-4f2fe3cb277b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.9986111111111, -179.99583333333334, -179.99305555555554,\n",
+       "       -179.99027777777778,           -179.9875, -179.98472222222222,\n",
+       "       -179.98194444444445, -179.97916666666666,  -179.9763888888889,\n",
+       "        -179.9736111111111,\n",
+       "       ...\n",
+       "         179.9736111111111,   179.9763888888889,  179.97916666666669,\n",
+       "        179.98194444444448,  179.98472222222222,            179.9875,\n",
+       "         179.9902777777778,  179.99305555555554,  179.99583333333334,\n",
+       "        179.99861111111113],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=129600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-efb32eb9-0c65-488b-a909-6dd075ffe338' class='xr-index-data-in' type='checkbox'/><label for='index-efb32eb9-0c65-488b-a909-6dd075ffe338' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1992-01-01&#x27;, &#x27;1993-01-01&#x27;, &#x27;1994-01-01&#x27;, &#x27;1995-01-01&#x27;,\n",
+       "               &#x27;1996-01-01&#x27;, &#x27;1997-01-01&#x27;, &#x27;1998-01-01&#x27;, &#x27;1999-01-01&#x27;,\n",
+       "               &#x27;2000-01-01&#x27;, &#x27;2001-01-01&#x27;, &#x27;2002-01-01&#x27;, &#x27;2003-01-01&#x27;,\n",
+       "               &#x27;2004-01-01&#x27;, &#x27;2005-01-01&#x27;, &#x27;2006-01-01&#x27;, &#x27;2007-01-01&#x27;,\n",
+       "               &#x27;2008-01-01&#x27;, &#x27;2009-01-01&#x27;, &#x27;2010-01-01&#x27;, &#x27;2011-01-01&#x27;,\n",
+       "               &#x27;2012-01-01&#x27;, &#x27;2013-01-01&#x27;, &#x27;2014-01-01&#x27;, &#x27;2015-01-01&#x27;,\n",
+       "               &#x27;2016-01-01&#x27;, &#x27;2017-01-01&#x27;, &#x27;2018-01-01&#x27;, &#x27;2019-01-01&#x27;,\n",
+       "               &#x27;2020-01-01&#x27;, &#x27;2021-01-01&#x27;, &#x27;2022-01-01&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-711510d7-ecc9-42ac-9fbe-401a31b6aae0' class='xr-section-summary-in' type='checkbox'  ><label for='section-711510d7-ecc9-42ac-9fbe-401a31b6aae0' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>TileSize :</span></dt><dd>2025:2025</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>https://www.ecmwf.int/en/about/contact-us/get-support</dd><dt><span>creation_date :</span></dt><dd>20181130T095451Z</dd><dt><span>creator_email :</span></dt><dd>landcover-cci@uclouvain.be</dd><dt><span>creator_name :</span></dt><dd>UCLouvain</dd><dt><span>creator_url :</span></dt><dd>http://www.uclouvain.be/</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>history :</span></dt><dd>amorgos-4,0, lc-sdr-1.0, lc-sr-1.0, lc-classification-1.0,lc-user-tools-3.13,lc-user-tools-4.3</dd><dt><span>id :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992-v2.0.7cds</dd><dt><span>institution :</span></dt><dd>UCLouvain</dd><dt><span>keywords :</span></dt><dd>land cover classification,satellite,observation</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>naming_authority :</span></dt><dd>org.esa-cci</dd><dt><span>product_version :</span></dt><dd>2.0.7cds</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-landcover-cci.org/</dd><dt><span>source :</span></dt><dd>MERIS FR L1B version 5.05, MERIS RR L1B version 8.0, SPOT VGT P</dd><dt><span>spatial_resolution :</span></dt><dd>300m</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Standard Names version 21</dd><dt><span>summary :</span></dt><dd>This dataset characterizes the land cover of a particular year (see time_coverage). The land cover was derived from the analysis of satellite data time series of the full period.</dd><dt><span>time_coverage_duration :</span></dt><dd>P1Y</dd><dt><span>time_coverage_end :</span></dt><dd>19921231</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1Y</dd><dt><span>time_coverage_start :</span></dt><dd>19920101</dd><dt><span>title :</span></dt><dd>Land Cover Map of ESA CCI brokered by CDS</dd><dt><span>tracking_id :</span></dt><dd>61b96fd7-42c3-4374-9de1-0dc3b0bcae2a</dd><dt><span>type :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 3TB\n",
+       "Dimensions:              (time: 31, lat: 64800, lon: 129600, bounds: 2)\n",
+       "Coordinates:\n",
+       "  * lat                  (lat) float64 518kB 90.0 90.0 89.99 ... -90.0 -90.0\n",
+       "  * lon                  (lon) float64 1MB -180.0 -180.0 -180.0 ... 180.0 180.0\n",
+       "  * time                 (time) datetime64[ns] 248B 1992-01-01 ... 2022-01-01\n",
+       "Dimensions without coordinates: bounds\n",
+       "Data variables:\n",
+       "    change_count         (time, lat, lon) uint8 260GB dask.array<chunksize=(1, 2025, 2025), meta=np.ndarray>\n",
+       "    crs                  int32 4B ...\n",
+       "    current_pixel_state  (time, lat, lon) float32 1TB dask.array<chunksize=(1, 2025, 2025), meta=np.ndarray>\n",
+       "    lat_bounds           (lat, bounds) float64 1MB dask.array<chunksize=(2025, 2), meta=np.ndarray>\n",
+       "    lccs_class           (time, lat, lon) uint8 260GB dask.array<chunksize=(1, 2025, 2025), meta=np.ndarray>\n",
+       "    lon_bounds           (lon, bounds) float64 2MB dask.array<chunksize=(2025, 2), meta=np.ndarray>\n",
+       "    observation_count    (time, lat, lon) uint16 521GB dask.array<chunksize=(1, 2025, 2025), meta=np.ndarray>\n",
+       "    processed_flag       (time, lat, lon) float32 1TB dask.array<chunksize=(1, 2025, 2025), meta=np.ndarray>\n",
+       "    time_bounds          (time, bounds) datetime64[ns] 496B dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "store = new_data_store(\"s3\", root=\"deep-esdl-public\")\n",
+    "mlds_lc = store.open_data(\"LC-1x2025x2025-2.0.0.levels\")\n",
+    "ds = mlds_lc.base_dataset\n",
+    "ds_time_slice = ds.sel(time=datetime(2022, 1, 1))\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28f43499-f72f-4ab8-8713-f4dde60ecaa1",
+   "metadata": {},
+   "source": [
+    "We generate a regular grid mapping covering Germany and demonstrate that the new `reproject_dataset` method produces results very similar to those of the `resample_in_space` method. \n",
+    "\n",
+    "As a first step, we create a regular grid mapping using the EPSG:3035 coordinate reference system."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a73e241f-8ead-4beb-94b4-1b3a612b6a8e",
+   "metadata": {
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 33.8 ms, sys: 1.07 ms, total: 34.9 ms\n",
+      "Wall time: 33.8 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "bbox = [5, 46, 15, 57]\n",
+    "target_crs = \"EPSG:3035\"\n",
+    "t = pyproj.Transformer.from_crs(\"EPSG:4326\", target_crs, always_xy=True)\n",
+    "target_bbox = t.transform_bounds(*bbox)\n",
+    "spatial_res = 150\n",
+    "x_size = int((target_bbox[2] - target_bbox[0]) / spatial_res) + 1\n",
+    "y_size = int(abs(target_bbox[3] - target_bbox[1]) / spatial_res) + 1\n",
+    "target_gm = GridMapping.regular(\n",
+    "    size=(x_size, y_size),\n",
+    "    xy_min=(target_bbox[0] - spatial_res / 2, target_bbox[1] - spatial_res / 2),\n",
+    "    xy_res=spatial_res,\n",
+    "    crs=target_crs,\n",
+    "    tile_size=4000,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "78f5149d-7522-447f-9a8c-d963d5c6d7e7",
+   "metadata": {},
+   "source": [
+    "Firstly, we apply the exsisting `resample_in_space` method, where we clip the source dataset. Otherwise, `resampling_in_space` would take for ever. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f66ecbb8-318a-4a5d-ab45-b7583176233e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 9.24 s, sys: 205 ms, total: 9.45 s\n",
+      "Wall time: 9.44 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 510MB\n",
+       "Dimensions:              (x: 5167, y: 8227, bounds: 2)\n",
+       "Coordinates:\n",
+       "    time                 datetime64[ns] 8B 2022-01-01\n",
+       "    spatial_ref          int64 8B 0\n",
+       "  * x                    (x) float64 41kB 3.934e+06 3.934e+06 ... 4.708e+06\n",
+       "  * y                    (y) float64 66kB 3.777e+06 3.777e+06 ... 2.543e+06\n",
+       "Dimensions without coordinates: bounds\n",
+       "Data variables:\n",
+       "    change_count         (y, x) uint8 43MB dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;\n",
+       "    current_pixel_state  (y, x) float32 170MB dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;\n",
+       "    lccs_class           (y, x) uint8 43MB dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;\n",
+       "    observation_count    (y, x) uint16 85MB dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;\n",
+       "    processed_flag       (y, x) float32 170MB dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;\n",
+       "    time_bounds          (bounds) datetime64[ns] 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-216129ca-9945-407a-9565-183466234026' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-216129ca-9945-407a-9565-183466234026' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 5167</li><li><span class='xr-has-index'>y</span>: 8227</li><li><span>bounds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d238f97b-a18a-4d3f-89a3-054dc3e11970' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d238f97b-a18a-4d3f-89a3-054dc3e11970' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01</div><input id='attrs-fdefa06c-3540-4924-90b0-17ed6bb3b780' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdefa06c-3540-4924-90b0-17ed6bb3b780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33340949-3dda-4bb9-a773-021c35a3d955' class='xr-var-data-in' type='checkbox'><label for='data-33340949-3dda-4bb9-a773-021c35a3d955' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-d3499e17-6c88-40c2-bf21-3b8c28b2d69a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3499e17-6c88-40c2-bf21-3b8c28b2d69a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ab6ab06-143f-4f45-bb21-a6cb5460a248' class='xr-var-data-in' type='checkbox'><label for='data-5ab6ab06-143f-4f45-bb21-a6cb5460a248' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;ETRS89-extended / LAEA Europe&quot;,BASEGEOGCRS[&quot;ETRS89&quot;,ENSEMBLE[&quot;European Terrestrial Reference System 1989 ensemble&quot;,MEMBER[&quot;European Terrestrial Reference Frame 1989&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1990&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1991&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1992&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1993&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1994&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1996&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1997&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2000&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2005&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2014&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2020&quot;],ELLIPSOID[&quot;GRS 1980&quot;,6378137,298.257222101,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[0.1]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4258]],CONVERSION[&quot;Europe Equal Area 2001&quot;,METHOD[&quot;Lambert Azimuthal Equal Area&quot;,ID[&quot;EPSG&quot;,9820]],PARAMETER[&quot;Latitude of natural origin&quot;,52,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,10,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;False easting&quot;,4321000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,3210000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;northing (Y)&quot;,north,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;easting (X)&quot;,east,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Statistical analysis.&quot;],AREA[&quot;Europe - European Union (EU) countries and candidates. Europe - onshore and offshore: Albania; Andorra; Austria; Belgium; Bosnia and Herzegovina; Bulgaria; Croatia; Cyprus; Czechia; Denmark; Estonia; Faroe Islands; Finland; France; Germany; Gibraltar; Greece; Hungary; Iceland; Ireland; Italy; Kosovo; Latvia; Liechtenstein; Lithuania; Luxembourg; Malta; Monaco; Montenegro; Netherlands; North Macedonia; Norway including Svalbard and Jan Mayen; Poland; Portugal including Madeira and Azores; Romania; San Marino; Serbia; Slovakia; Slovenia; Spain including Canary Islands; Sweden; Switzerland; Türkiye (Turkey); United Kingdom (UK) including Channel Islands and Isle of Man; Vatican City State.&quot;],BBOX[24.6,-35.58,84.73,44.83]],ID[&quot;EPSG&quot;,3035]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314140356</dd><dt><span>inverse_flattening :</span></dt><dd>298.257222101</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>GRS 1980</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>ETRS89</dd><dt><span>horizontal_datum_name :</span></dt><dd>European Terrestrial Reference System 1989 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>ETRS89-extended / LAEA Europe</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>52.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>4321000.0</dd><dt><span>false_northing :</span></dt><dd>3210000.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.934e+06 3.934e+06 ... 4.708e+06</div><input id='attrs-8183e241-1dd7-47e6-857a-3bf166a8d12c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8183e241-1dd7-47e6-857a-3bf166a8d12c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d787c3c4-3b16-4865-bc5a-24fa37747f37' class='xr-var-data-in' type='checkbox'><label for='data-d787c3c4-3b16-4865-bc5a-24fa37747f37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3933529., 3933679., 3933829., ..., 4708129., 4708279., 4708429.],\n",
+       "      shape=(5167,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.777e+06 3.777e+06 ... 2.543e+06</div><input id='attrs-52d7c35c-3d9e-4b66-8757-856bca3487dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52d7c35c-3d9e-4b66-8757-856bca3487dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5549a2a9-3e63-4f5e-a0aa-b86069097f83' class='xr-var-data-in' type='checkbox'><label for='data-5549a2a9-3e63-4f5e-a0aa-b86069097f83' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3776909., 3776759., 3776609., ..., 2543309., 2543159., 2543009.],\n",
+       "      shape=(8227,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d18e7f18-44c0-4a4c-a46c-273edbfc1c53' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d18e7f18-44c0-4a4c-a46c-273edbfc1c53' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>change_count</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-aabd5ceb-3867-4d24-88c5-231a071c9ab4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aabd5ceb-3867-4d24-88c5-231a071c9ab4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c9cd1f1-d59c-4744-8907-bf64c44cb760' class='xr-var-data-in' type='checkbox'><label for='data-6c9cd1f1-d59c-4744-8907-bf64c44cb760' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>number of class changes</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 40.54 MiB </td>\n",
+       "                        <td> 15.26 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (8227, 5167) </td>\n",
+       "                        <td> (4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 6 chunks in 21 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"58\" x2=\"75\" y2=\"58\" />\n",
+       "  <line x1=\"0\" y1=\"116\" x2=\"75\" y2=\"116\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.36647623678132,0.0 75.36647623678132,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.683238\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >5167</text>\n",
+       "  <text x=\"95.366476\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.366476,60.000000)\">8227</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>current_pixel_state</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-2d970e53-2710-428c-96b4-a78bd725d403' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d970e53-2710-428c-96b4-a78bd725d403' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-753fe1dc-0041-4943-95a0-2fb2fc1e67d0' class='xr-var-data-in' type='checkbox'><label for='data-753fe1dc-0041-4943-95a0-2fb2fc1e67d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_meanings :</span></dt><dd>invalid clear_land clear_water clear_snow_ice cloud cloud_shadow</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3, 4, 5]</dd><dt><span>long_name :</span></dt><dd>LC pixel type mask</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs status_flag</dd><dt><span>valid_max :</span></dt><dd>5</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 162.16 MiB </td>\n",
+       "                        <td> 61.04 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (8227, 5167) </td>\n",
+       "                        <td> (4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 6 chunks in 21 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"58\" x2=\"75\" y2=\"58\" />\n",
+       "  <line x1=\"0\" y1=\"116\" x2=\"75\" y2=\"116\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.36647623678132,0.0 75.36647623678132,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.683238\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >5167</text>\n",
+       "  <text x=\"95.366476\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.366476,60.000000)\">8227</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lccs_class</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-696afef3-5d7b-4a77-9234-9d7ac5c7f3f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-696afef3-5d7b-4a77-9234-9d7ac5c7f3f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1efadf0e-f6f3-487b-b486-cd7664d652ea' class='xr-var-data-in' type='checkbox'><label for='data-1efadf0e-f6f3-487b-b486-cd7664d652ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ancillary_variables :</span></dt><dd>processed_flag current_pixel_state observation_count change_count</dd><dt><span>flag_colors :</span></dt><dd>#ffff64 #ffff64 #ffff00 #aaf0f0 #dcf064 #c8c864 #006400 #00a000 #00a000 #aac800 #003c00 #003c00 #005000 #285000 #285000 #286400 #788200 #8ca000 #be9600 #966400 #966400 #966400 #ffb432 #ffdcd2 #ffebaf #ffc864 #ffd278 #ffebaf #00785a #009678 #00dc82 #c31400 #fff5d7 #dcdcdc #fff5d7 #0046c8 #ffffff</dd><dt><span>flag_meanings :</span></dt><dd>no_data cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban bare_areas bare_areas_consolidated bare_areas_unconsolidated water snow_and_ice</dd><dt><span>flag_values :</span></dt><dd>[0, 10, 11, 12, 20, 30, 40, 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100, 110, 120, 121, 122, 130, 140, 150, 151, 152, 153, 160, 170, 180, 190, 200, 201, 202, 210, 220]</dd><dt><span>long_name :</span></dt><dd>Land cover class defined in LCCS</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs</dd><dt><span>valid_max :</span></dt><dd>220</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 40.54 MiB </td>\n",
+       "                        <td> 15.26 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (8227, 5167) </td>\n",
+       "                        <td> (4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 6 chunks in 21 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"58\" x2=\"75\" y2=\"58\" />\n",
+       "  <line x1=\"0\" y1=\"116\" x2=\"75\" y2=\"116\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.36647623678132,0.0 75.36647623678132,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.683238\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >5167</text>\n",
+       "  <text x=\"95.366476\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.366476,60.000000)\">8227</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>observation_count</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-ad105f78-0386-4184-ab13-a4d003374a03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad105f78-0386-4184-ab13-a4d003374a03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00e48f23-edfc-4924-91b4-162481db17f0' class='xr-var-data-in' type='checkbox'><label for='data-00e48f23-edfc-4924-91b4-162481db17f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>number of valid observations</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs number_of_observations</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 81.08 MiB </td>\n",
+       "                        <td> 30.52 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (8227, 5167) </td>\n",
+       "                        <td> (4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 6 chunks in 21 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"58\" x2=\"75\" y2=\"58\" />\n",
+       "  <line x1=\"0\" y1=\"116\" x2=\"75\" y2=\"116\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.36647623678132,0.0 75.36647623678132,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.683238\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >5167</text>\n",
+       "  <text x=\"95.366476\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.366476,60.000000)\">8227</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>processed_flag</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-0298903f-5428-4e67-afd9-9400c0c85d74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0298903f-5428-4e67-afd9-9400c0c85d74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62718147-eefe-4b60-a46d-cd610e81c72e' class='xr-var-data-in' type='checkbox'><label for='data-62718147-eefe-4b60-a46d-cd610e81c72e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_meanings :</span></dt><dd>not_processed processed</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>long_name :</span></dt><dd>LC map processed area flag</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs status_flag</dd><dt><span>valid_max :</span></dt><dd>1</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 162.16 MiB </td>\n",
+       "                        <td> 61.04 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (8227, 5167) </td>\n",
+       "                        <td> (4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 6 chunks in 21 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"125\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"75\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"58\" x2=\"75\" y2=\"58\" />\n",
+       "  <line x1=\"0\" y1=\"116\" x2=\"75\" y2=\"116\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"58\" y2=\"120\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 75.36647623678132,0.0 75.36647623678132,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"37.683238\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >5167</text>\n",
+       "  <text x=\"95.366476\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,95.366476,60.000000)\">8227</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bounds</span></div><div class='xr-var-dims'>(bounds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-ba037132-afc2-4a36-9c55-14db764da489' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba037132-afc2-4a36-9c55-14db764da489' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53243ed8-6a99-42c9-899e-b3101bc36f47' class='xr-var-data-in' type='checkbox'><label for='data-53243ed8-6a99-42c9-899e-b3101bc36f47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-412bd3a3-2576-47c4-b89e-7a211ad8ffa1' class='xr-section-summary-in' type='checkbox'  ><label for='section-412bd3a3-2576-47c4-b89e-7a211ad8ffa1' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b63f9134-9c2a-497e-b111-b82686596b48' class='xr-index-data-in' type='checkbox'/><label for='index-b63f9134-9c2a-497e-b111-b82686596b48' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([3933529.0, 3933679.0, 3933829.0, 3933979.0, 3934129.0, 3934279.0,\n",
+       "       3934429.0, 3934579.0, 3934729.0, 3934879.0,\n",
+       "       ...\n",
+       "       4707079.0, 4707229.0, 4707379.0, 4707529.0, 4707679.0, 4707829.0,\n",
+       "       4707979.0, 4708129.0, 4708279.0, 4708429.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=5167))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c269c4c8-0dd1-4864-9d58-b2260f811f0b' class='xr-index-data-in' type='checkbox'/><label for='index-c269c4c8-0dd1-4864-9d58-b2260f811f0b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([3776909.0, 3776759.0, 3776609.0, 3776459.0, 3776309.0, 3776159.0,\n",
+       "       3776009.0, 3775859.0, 3775709.0, 3775559.0,\n",
+       "       ...\n",
+       "       2544359.0, 2544209.0, 2544059.0, 2543909.0, 2543759.0, 2543609.0,\n",
+       "       2543459.0, 2543309.0, 2543159.0, 2543009.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=8227))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f0ac17b-f3a4-4088-8aa1-4864f314894f' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f0ac17b-f3a4-4088-8aa1-4864f314894f' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>TileSize :</span></dt><dd>2025:2025</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>https://www.ecmwf.int/en/about/contact-us/get-support</dd><dt><span>creation_date :</span></dt><dd>20181130T095451Z</dd><dt><span>creator_email :</span></dt><dd>landcover-cci@uclouvain.be</dd><dt><span>creator_name :</span></dt><dd>UCLouvain</dd><dt><span>creator_url :</span></dt><dd>http://www.uclouvain.be/</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>history :</span></dt><dd>amorgos-4,0, lc-sdr-1.0, lc-sr-1.0, lc-classification-1.0,lc-user-tools-3.13,lc-user-tools-4.3</dd><dt><span>id :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992-v2.0.7cds</dd><dt><span>institution :</span></dt><dd>UCLouvain</dd><dt><span>keywords :</span></dt><dd>land cover classification,satellite,observation</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>naming_authority :</span></dt><dd>org.esa-cci</dd><dt><span>product_version :</span></dt><dd>2.0.7cds</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-landcover-cci.org/</dd><dt><span>source :</span></dt><dd>MERIS FR L1B version 5.05, MERIS RR L1B version 8.0, SPOT VGT P</dd><dt><span>spatial_resolution :</span></dt><dd>300m</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Standard Names version 21</dd><dt><span>summary :</span></dt><dd>This dataset characterizes the land cover of a particular year (see time_coverage). The land cover was derived from the analysis of satellite data time series of the full period.</dd><dt><span>time_coverage_duration :</span></dt><dd>P1Y</dd><dt><span>time_coverage_end :</span></dt><dd>19921231</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1Y</dd><dt><span>time_coverage_start :</span></dt><dd>19920101</dd><dt><span>title :</span></dt><dd>Land Cover Map of ESA CCI brokered by CDS</dd><dt><span>tracking_id :</span></dt><dd>61b96fd7-42c3-4374-9de1-0dc3b0bcae2a</dd><dt><span>type :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 510MB\n",
+       "Dimensions:              (x: 5167, y: 8227, bounds: 2)\n",
+       "Coordinates:\n",
+       "    time                 datetime64[ns] 8B 2022-01-01\n",
+       "    spatial_ref          int64 8B 0\n",
+       "  * x                    (x) float64 41kB 3.934e+06 3.934e+06 ... 4.708e+06\n",
+       "  * y                    (y) float64 66kB 3.777e+06 3.777e+06 ... 2.543e+06\n",
+       "Dimensions without coordinates: bounds\n",
+       "Data variables:\n",
+       "    change_count         (y, x) uint8 43MB dask.array<chunksize=(4000, 4000), meta=np.ndarray>\n",
+       "    current_pixel_state  (y, x) float32 170MB dask.array<chunksize=(4000, 4000), meta=np.ndarray>\n",
+       "    lccs_class           (y, x) uint8 43MB dask.array<chunksize=(4000, 4000), meta=np.ndarray>\n",
+       "    observation_count    (y, x) uint16 85MB dask.array<chunksize=(4000, 4000), meta=np.ndarray>\n",
+       "    processed_flag       (y, x) float32 170MB dask.array<chunksize=(4000, 4000), meta=np.ndarray>\n",
+       "    time_bounds          (bounds) datetime64[ns] 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds_resampling = resample_in_space(ds_time_slice, target_gm=target_gm)\n",
+    "ds_resampling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "79654851-987a-4739-883f-257d9399840f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 6.74 s, sys: 805 ms, total: 7.55 s\n",
+      "Wall time: 3.48 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x758de04f27b0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds_resampling.lccs_class[::5, ::5].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3ea8eda6-fae6-4507-9f16-d68bf1ec08db",
+   "metadata": {},
+   "source": [
+    "The `reproject_dataset` method can handle source datasets of any size. It automatically selects the overlapping portions of the source dataset that intersect with the target grid mapping.\n",
+    "\n",
+    "If the extent of the source dataset is too small and the target grid mapping extends beyond its boundaries, padding with a fill value is required. This fill value can either be provided by the user or is determined by the data type of the data array, as described in the docstring of the `reproject_dataset` method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9ab6a365-62a7-4fc7-a454-3f5fd62b0996",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 36.2 ms, sys: 8.95 ms, total: 45.1 ms\n",
+      "Wall time: 44.9 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 42GB\n",
+       "Dimensions:     (time: 5, lat: 64800, lon: 129600)\n",
+       "Coordinates:\n",
+       "  * lat         (lat) float64 518kB 90.0 90.0 89.99 89.99 ... -89.99 -90.0 -90.0\n",
+       "  * lon         (lon) float64 1MB -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "  * time        (time) datetime64[ns] 40B 2018-01-01 2019-01-01 ... 2022-01-01\n",
+       "Data variables:\n",
+       "    lccs_class  (time, lat, lon) uint8 42GB dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-887fc424-682f-41a7-88a3-6d685a0eba60' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-887fc424-682f-41a7-88a3-6d685a0eba60' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>lat</span>: 64800</li><li><span class='xr-has-index'>lon</span>: 129600</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e82348b8-6003-4c7a-8355-59c618786a9f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e82348b8-6003-4c7a-8355-59c618786a9f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 90.0 89.99 ... -90.0 -90.0</div><input id='attrs-548f27c8-1844-43f3-9d4c-e44414095a62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-548f27c8-1844-43f3-9d4c-e44414095a62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6da62e28-0712-4cc8-b16f-fe042fac4899' class='xr-var-data-in' type='checkbox'><label for='data-6da62e28-0712-4cc8-b16f-fe042fac4899' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bounds</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([ 89.998611,  89.995833,  89.993056, ..., -89.993056, -89.995833,\n",
+       "       -89.998611], shape=(64800,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-11d284f8-c2e0-4044-a77b-5442f101e7d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11d284f8-c2e0-4044-a77b-5442f101e7d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb6e5a3d-f022-4599-a7e2-d50cd390e605' class='xr-var-data-in' type='checkbox'><label for='data-cb6e5a3d-f022-4599-a7e2-d50cd390e605' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bounds</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([-179.998611, -179.995833, -179.993056, ...,  179.993056,  179.995833,\n",
+       "        179.998611], shape=(129600,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01 ... 2022-01-01</div><input id='attrs-f0674176-08a2-4bf2-a97a-3dd4e86f7ec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0674176-08a2-4bf2-a97a-3dd4e86f7ec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f84ff7a-341c-44a3-b58d-895c068fc25b' class='xr-var-data-in' type='checkbox'><label for='data-5f84ff7a-341c-44a3-b58d-895c068fc25b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-969241d1-c9a1-4912-b8bd-331ded517b18' class='xr-section-summary-in' type='checkbox'  checked><label for='section-969241d1-c9a1-4912-b8bd-331ded517b18' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lccs_class</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2025, 2025), meta=np.ndarray&gt;</div><input id='attrs-bba1e70c-3f05-46e3-b014-9a9843f6fcaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bba1e70c-3f05-46e3-b014-9a9843f6fcaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8eccab56-359d-4cf3-8c85-963569d24276' class='xr-var-data-in' type='checkbox'><label for='data-8eccab56-359d-4cf3-8c85-963569d24276' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ancillary_variables :</span></dt><dd>processed_flag current_pixel_state observation_count change_count</dd><dt><span>flag_colors :</span></dt><dd>#ffff64 #ffff64 #ffff00 #aaf0f0 #dcf064 #c8c864 #006400 #00a000 #00a000 #aac800 #003c00 #003c00 #005000 #285000 #285000 #286400 #788200 #8ca000 #be9600 #966400 #966400 #966400 #ffb432 #ffdcd2 #ffebaf #ffc864 #ffd278 #ffebaf #00785a #009678 #00dc82 #c31400 #fff5d7 #dcdcdc #fff5d7 #0046c8 #ffffff</dd><dt><span>flag_meanings :</span></dt><dd>no_data cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban bare_areas bare_areas_consolidated bare_areas_unconsolidated water snow_and_ice</dd><dt><span>flag_values :</span></dt><dd>[0, 10, 11, 12, 20, 30, 40, 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100, 110, 120, 121, 122, 130, 140, 150, 151, 152, 153, 160, 170, 180, 190, 200, 201, 202, 210, 220]</dd><dt><span>long_name :</span></dt><dd>Land cover class defined in LCCS</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs</dd><dt><span>valid_max :</span></dt><dd>220</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 39.11 GiB </td>\n",
+       "                        <td> 3.91 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (5, 64800, 129600) </td>\n",
+       "                        <td> (1, 2025, 2025) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 10240 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"124\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"1\" x2=\"24\" y2=\"16\" />\n",
+       "  <line x1=\"10\" y1=\"5\" x2=\"24\" y2=\"20\" />\n",
+       "  <line x1=\"10\" y1=\"9\" x2=\"24\" y2=\"24\" />\n",
+       "  <line x1=\"10\" y1=\"11\" x2=\"24\" y2=\"26\" />\n",
+       "  <line x1=\"10\" y1=\"15\" x2=\"24\" y2=\"29\" />\n",
+       "  <line x1=\"10\" y1=\"18\" x2=\"24\" y2=\"33\" />\n",
+       "  <line x1=\"10\" y1=\"20\" x2=\"24\" y2=\"35\" />\n",
+       "  <line x1=\"10\" y1=\"24\" x2=\"24\" y2=\"39\" />\n",
+       "  <line x1=\"10\" y1=\"28\" x2=\"24\" y2=\"43\" />\n",
+       "  <line x1=\"10\" y1=\"30\" x2=\"24\" y2=\"44\" />\n",
+       "  <line x1=\"10\" y1=\"33\" x2=\"24\" y2=\"48\" />\n",
+       "  <line x1=\"10\" y1=\"37\" x2=\"24\" y2=\"52\" />\n",
+       "  <line x1=\"10\" y1=\"39\" x2=\"24\" y2=\"54\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"46\" x2=\"24\" y2=\"61\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"52\" x2=\"24\" y2=\"67\" />\n",
+       "  <line x1=\"10\" y1=\"56\" x2=\"24\" y2=\"71\" />\n",
+       "  <line x1=\"10\" y1=\"60\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"62\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"65\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"68\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,74.9485979497544 10.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"135\" y2=\"5\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"138\" y2=\"8\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"15\" y1=\"0\" x2=\"30\" y2=\"14\" />\n",
+       "  <line x1=\"21\" y1=\"0\" x2=\"36\" y2=\"14\" />\n",
+       "  <line x1=\"28\" y1=\"0\" x2=\"43\" y2=\"14\" />\n",
+       "  <line x1=\"34\" y1=\"0\" x2=\"49\" y2=\"14\" />\n",
+       "  <line x1=\"40\" y1=\"0\" x2=\"54\" y2=\"14\" />\n",
+       "  <line x1=\"47\" y1=\"0\" x2=\"62\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"58\" y1=\"0\" x2=\"73\" y2=\"14\" />\n",
+       "  <line x1=\"66\" y1=\"0\" x2=\"81\" y2=\"14\" />\n",
+       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
+       "  <line x1=\"79\" y1=\"0\" x2=\"94\" y2=\"14\" />\n",
+       "  <line x1=\"85\" y1=\"0\" x2=\"99\" y2=\"14\" />\n",
+       "  <line x1=\"90\" y1=\"0\" x2=\"105\" y2=\"14\" />\n",
+       "  <line x1=\"98\" y1=\"0\" x2=\"113\" y2=\"14\" />\n",
+       "  <line x1=\"103\" y1=\"0\" x2=\"118\" y2=\"14\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"124\" y2=\"14\" />\n",
+       "  <line x1=\"116\" y1=\"0\" x2=\"131\" y2=\"14\" />\n",
+       "  <line x1=\"122\" y1=\"0\" x2=\"137\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"16\" x2=\"144\" y2=\"16\" />\n",
+       "  <line x1=\"24\" y1=\"20\" x2=\"144\" y2=\"20\" />\n",
+       "  <line x1=\"24\" y1=\"24\" x2=\"144\" y2=\"24\" />\n",
+       "  <line x1=\"24\" y1=\"26\" x2=\"144\" y2=\"26\" />\n",
+       "  <line x1=\"24\" y1=\"29\" x2=\"144\" y2=\"29\" />\n",
+       "  <line x1=\"24\" y1=\"33\" x2=\"144\" y2=\"33\" />\n",
+       "  <line x1=\"24\" y1=\"35\" x2=\"144\" y2=\"35\" />\n",
+       "  <line x1=\"24\" y1=\"39\" x2=\"144\" y2=\"39\" />\n",
+       "  <line x1=\"24\" y1=\"43\" x2=\"144\" y2=\"43\" />\n",
+       "  <line x1=\"24\" y1=\"44\" x2=\"144\" y2=\"44\" />\n",
+       "  <line x1=\"24\" y1=\"48\" x2=\"144\" y2=\"48\" />\n",
+       "  <line x1=\"24\" y1=\"52\" x2=\"144\" y2=\"52\" />\n",
+       "  <line x1=\"24\" y1=\"54\" x2=\"144\" y2=\"54\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"144\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"61\" x2=\"144\" y2=\"61\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"67\" x2=\"144\" y2=\"67\" />\n",
+       "  <line x1=\"24\" y1=\"71\" x2=\"144\" y2=\"71\" />\n",
+       "  <line x1=\"24\" y1=\"74\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"14\" x2=\"30\" y2=\"74\" />\n",
+       "  <line x1=\"36\" y1=\"14\" x2=\"36\" y2=\"74\" />\n",
+       "  <line x1=\"43\" y1=\"14\" x2=\"43\" y2=\"74\" />\n",
+       "  <line x1=\"49\" y1=\"14\" x2=\"49\" y2=\"74\" />\n",
+       "  <line x1=\"54\" y1=\"14\" x2=\"54\" y2=\"74\" />\n",
+       "  <line x1=\"62\" y1=\"14\" x2=\"62\" y2=\"74\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"74\" />\n",
+       "  <line x1=\"73\" y1=\"14\" x2=\"73\" y2=\"74\" />\n",
+       "  <line x1=\"81\" y1=\"14\" x2=\"81\" y2=\"74\" />\n",
+       "  <line x1=\"86\" y1=\"14\" x2=\"86\" y2=\"74\" />\n",
+       "  <line x1=\"94\" y1=\"14\" x2=\"94\" y2=\"74\" />\n",
+       "  <line x1=\"99\" y1=\"14\" x2=\"99\" y2=\"74\" />\n",
+       "  <line x1=\"105\" y1=\"14\" x2=\"105\" y2=\"74\" />\n",
+       "  <line x1=\"113\" y1=\"14\" x2=\"113\" y2=\"74\" />\n",
+       "  <line x1=\"118\" y1=\"14\" x2=\"118\" y2=\"74\" />\n",
+       "  <line x1=\"124\" y1=\"14\" x2=\"124\" y2=\"74\" />\n",
+       "  <line x1=\"131\" y1=\"14\" x2=\"131\" y2=\"74\" />\n",
+       "  <line x1=\"137\" y1=\"14\" x2=\"137\" y2=\"74\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"74\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,74.9485979497544 24.9485979497544,74.9485979497544\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"94.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >129600</text>\n",
+       "  <text x=\"164.948598\" y=\"44.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,44.948598)\">64800</text>\n",
+       "  <text x=\"7.474299\" y=\"87.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,87.474299)\">5</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-52e274a6-ffd3-4038-820f-eb2834d0ce89' class='xr-section-summary-in' type='checkbox'  ><label for='section-52e274a6-ffd3-4038-820f-eb2834d0ce89' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0139b5c0-4515-4a99-8394-81c1befdd76c' class='xr-index-data-in' type='checkbox'/><label for='index-0139b5c0-4515-4a99-8394-81c1befdd76c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 89.99861111111113,  89.99583333333334,  89.99305555555557,\n",
+       "        89.99027777777778,  89.98750000000001,  89.98472222222222,\n",
+       "        89.98194444444445,  89.97916666666669,  89.97638888888889,\n",
+       "        89.97361111111113,\n",
+       "       ...\n",
+       "       -89.97361111111111, -89.97638888888889, -89.97916666666667,\n",
+       "       -89.98194444444445, -89.98472222222222,           -89.9875,\n",
+       "       -89.99027777777778, -89.99305555555556, -89.99583333333334,\n",
+       "       -89.99861111111112],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=64800))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f76b6548-2a75-46d3-99ed-4e40159f637a' class='xr-index-data-in' type='checkbox'/><label for='index-f76b6548-2a75-46d3-99ed-4e40159f637a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -179.9986111111111, -179.99583333333334, -179.99305555555554,\n",
+       "       -179.99027777777778,           -179.9875, -179.98472222222222,\n",
+       "       -179.98194444444445, -179.97916666666666,  -179.9763888888889,\n",
+       "        -179.9736111111111,\n",
+       "       ...\n",
+       "         179.9736111111111,   179.9763888888889,  179.97916666666669,\n",
+       "        179.98194444444448,  179.98472222222222,            179.9875,\n",
+       "         179.9902777777778,  179.99305555555554,  179.99583333333334,\n",
+       "        179.99861111111113],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=129600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b4048775-330f-4fd1-85ec-eb37e9420aca' class='xr-index-data-in' type='checkbox'/><label for='index-b4048775-330f-4fd1-85ec-eb37e9420aca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2018-01-01&#x27;, &#x27;2019-01-01&#x27;, &#x27;2020-01-01&#x27;, &#x27;2021-01-01&#x27;,\n",
+       "               &#x27;2022-01-01&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2d38093-6841-4e1f-bfef-50c6cb04cf84' class='xr-section-summary-in' type='checkbox'  ><label for='section-b2d38093-6841-4e1f-bfef-50c6cb04cf84' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>TileSize :</span></dt><dd>2025:2025</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>https://www.ecmwf.int/en/about/contact-us/get-support</dd><dt><span>creation_date :</span></dt><dd>20181130T095451Z</dd><dt><span>creator_email :</span></dt><dd>landcover-cci@uclouvain.be</dd><dt><span>creator_name :</span></dt><dd>UCLouvain</dd><dt><span>creator_url :</span></dt><dd>http://www.uclouvain.be/</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>history :</span></dt><dd>amorgos-4,0, lc-sdr-1.0, lc-sr-1.0, lc-classification-1.0,lc-user-tools-3.13,lc-user-tools-4.3</dd><dt><span>id :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992-v2.0.7cds</dd><dt><span>institution :</span></dt><dd>UCLouvain</dd><dt><span>keywords :</span></dt><dd>land cover classification,satellite,observation</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>naming_authority :</span></dt><dd>org.esa-cci</dd><dt><span>product_version :</span></dt><dd>2.0.7cds</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-landcover-cci.org/</dd><dt><span>source :</span></dt><dd>MERIS FR L1B version 5.05, MERIS RR L1B version 8.0, SPOT VGT P</dd><dt><span>spatial_resolution :</span></dt><dd>300m</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Standard Names version 21</dd><dt><span>summary :</span></dt><dd>This dataset characterizes the land cover of a particular year (see time_coverage). The land cover was derived from the analysis of satellite data time series of the full period.</dd><dt><span>time_coverage_duration :</span></dt><dd>P1Y</dd><dt><span>time_coverage_end :</span></dt><dd>19921231</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1Y</dd><dt><span>time_coverage_start :</span></dt><dd>19920101</dd><dt><span>title :</span></dt><dd>Land Cover Map of ESA CCI brokered by CDS</dd><dt><span>tracking_id :</span></dt><dd>61b96fd7-42c3-4374-9de1-0dc3b0bcae2a</dd><dt><span>type :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 42GB\n",
+       "Dimensions:     (time: 5, lat: 64800, lon: 129600)\n",
+       "Coordinates:\n",
+       "  * lat         (lat) float64 518kB 90.0 90.0 89.99 89.99 ... -89.99 -90.0 -90.0\n",
+       "  * lon         (lon) float64 1MB -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "  * time        (time) datetime64[ns] 40B 2018-01-01 2019-01-01 ... 2022-01-01\n",
+       "Data variables:\n",
+       "    lccs_class  (time, lat, lon) uint8 42GB dask.array<chunksize=(1, 2025, 2025), meta=np.ndarray>\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds = ds.sel(time=slice(datetime(2018, 1, 1), datetime(2022, 1, 1)))\n",
+    "ds = ds[[\"lccs_class\"]]\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a1ca3fd7-d0e2-4bad-bfbc-65111751e659",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 18.3 ms, sys: 3.03 ms, total: 21.3 ms\n",
+      "Wall time: 20.5 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "class: **RegularGridMapping**\n",
+       "* is_regular: True\n",
+       "* is_j_axis_up: False\n",
+       "* is_lon_360: False\n",
+       "* crs: EPSG:3035\n",
+       "* xy_res: (300, 300)\n",
+       "* xy_bbox: (1287527, 239402, 7354427, 6906902)\n",
+       "* ij_bbox: (0, 0, 20223, 22225)\n",
+       "* xy_dim_names: ('x', 'y')\n",
+       "* xy_var_names: ('x', 'y')\n",
+       "* size: (20223, 22225)\n",
+       "* tile_size: (4000, 4000)"
+      ],
+      "text/plain": [
+       "<xcube_resampling.gridmapping.regular.RegularGridMapping at 0x758de381fed0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "bbox = [-20, 25, 40, 85]\n",
+    "target_crs = \"EPSG:3035\"\n",
+    "t = pyproj.Transformer.from_crs(\"EPSG:4326\", target_crs, always_xy=True)\n",
+    "target_bbox = t.transform_bounds(*bbox)\n",
+    "spatial_res = 300\n",
+    "x_size = int((target_bbox[2] - target_bbox[0]) / spatial_res) + 1\n",
+    "y_size = int(abs(target_bbox[3] - target_bbox[1]) / spatial_res) + 1\n",
+    "target_gm = GridMapping.regular(\n",
+    "    size=(x_size, y_size),\n",
+    "    xy_min=(target_bbox[0] - spatial_res / 2, target_bbox[1] - spatial_res / 2),\n",
+    "    xy_res=spatial_res,\n",
+    "    crs=target_crs,\n",
+    "    tile_size=4000,\n",
+    ")\n",
+    "target_gm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "76645d9a-94e3-482c-8775-f2b69cd4ad43",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 13.9 s, sys: 101 ms, total: 14 s\n",
+      "Wall time: 14 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
+       "Dimensions:      (time: 5, x: 20223, y: 22225)\n",
+       "Coordinates:\n",
+       "  * time         (time) datetime64[ns] 40B 2018-01-01 2019-01-01 ... 2022-01-01\n",
+       "    spatial_ref  int64 8B 0\n",
+       "  * x            (x) float64 162kB 1.288e+06 1.288e+06 ... 7.354e+06 7.354e+06\n",
+       "  * y            (y) float64 178kB 6.907e+06 6.906e+06 ... 2.399e+05 2.396e+05\n",
+       "Data variables:\n",
+       "    lccs_class   (time, y, x) uint8 2GB dask.array&lt;chunksize=(1, 4000, 4000), meta=np.ndarray&gt;\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f5a53a0b-66c9-4dba-8107-0bae30ba6104' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f5a53a0b-66c9-4dba-8107-0bae30ba6104' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>x</span>: 20223</li><li><span class='xr-has-index'>y</span>: 22225</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f4dddad6-6d92-4555-9ed8-8a7357350288' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f4dddad6-6d92-4555-9ed8-8a7357350288' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01 ... 2022-01-01</div><input id='attrs-49f5118c-23c7-48b4-a975-3ebf85443c1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49f5118c-23c7-48b4-a975-3ebf85443c1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a875eb7-50e2-4743-bf32-39f81705ce0b' class='xr-var-data-in' type='checkbox'><label for='data-1a875eb7-50e2-4743-bf32-39f81705ce0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-98442b9a-3b60-4624-b3ba-7c4062ddb6f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98442b9a-3b60-4624-b3ba-7c4062ddb6f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6d63e9e-0945-431a-8ae5-31d0584872c5' class='xr-var-data-in' type='checkbox'><label for='data-a6d63e9e-0945-431a-8ae5-31d0584872c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;ETRS89-extended / LAEA Europe&quot;,BASEGEOGCRS[&quot;ETRS89&quot;,ENSEMBLE[&quot;European Terrestrial Reference System 1989 ensemble&quot;,MEMBER[&quot;European Terrestrial Reference Frame 1989&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1990&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1991&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1992&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1993&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1994&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1996&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1997&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2000&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2005&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2014&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2020&quot;],ELLIPSOID[&quot;GRS 1980&quot;,6378137,298.257222101,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[0.1]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4258]],CONVERSION[&quot;Europe Equal Area 2001&quot;,METHOD[&quot;Lambert Azimuthal Equal Area&quot;,ID[&quot;EPSG&quot;,9820]],PARAMETER[&quot;Latitude of natural origin&quot;,52,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,10,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;False easting&quot;,4321000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,3210000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;northing (Y)&quot;,north,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;easting (X)&quot;,east,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Statistical analysis.&quot;],AREA[&quot;Europe - European Union (EU) countries and candidates. Europe - onshore and offshore: Albania; Andorra; Austria; Belgium; Bosnia and Herzegovina; Bulgaria; Croatia; Cyprus; Czechia; Denmark; Estonia; Faroe Islands; Finland; France; Germany; Gibraltar; Greece; Hungary; Iceland; Ireland; Italy; Kosovo; Latvia; Liechtenstein; Lithuania; Luxembourg; Malta; Monaco; Montenegro; Netherlands; North Macedonia; Norway including Svalbard and Jan Mayen; Poland; Portugal including Madeira and Azores; Romania; San Marino; Serbia; Slovakia; Slovenia; Spain including Canary Islands; Sweden; Switzerland; Türkiye (Turkey); United Kingdom (UK) including Channel Islands and Isle of Man; Vatican City State.&quot;],BBOX[24.6,-35.58,84.73,44.83]],ID[&quot;EPSG&quot;,3035]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314140356</dd><dt><span>inverse_flattening :</span></dt><dd>298.257222101</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>GRS 1980</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>ETRS89</dd><dt><span>horizontal_datum_name :</span></dt><dd>European Terrestrial Reference System 1989 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>ETRS89-extended / LAEA Europe</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>52.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>4321000.0</dd><dt><span>false_northing :</span></dt><dd>3210000.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.288e+06 1.288e+06 ... 7.354e+06</div><input id='attrs-4266a987-7d6c-41c7-9fd6-4186dfc4e820' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4266a987-7d6c-41c7-9fd6-4186dfc4e820' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d0540d8-33d6-4802-b181-a21cabbb27bd' class='xr-var-data-in' type='checkbox'><label for='data-2d0540d8-33d6-4802-b181-a21cabbb27bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1287677., 1287977., 1288277., ..., 7353677., 7353977., 7354277.],\n",
+       "      shape=(20223,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.907e+06 6.906e+06 ... 2.396e+05</div><input id='attrs-48f4b033-efea-4114-aa3c-747bf471982a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48f4b033-efea-4114-aa3c-747bf471982a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a84cb1f-5a2d-414a-a2a8-a0ba1de3447e' class='xr-var-data-in' type='checkbox'><label for='data-1a84cb1f-5a2d-414a-a2a8-a0ba1de3447e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6906752., 6906452., 6906152., ...,  240152.,  239852.,  239552.],\n",
+       "      shape=(22225,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c55b16d7-dbad-4116-be30-263f972ff1a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c55b16d7-dbad-4116-be30-263f972ff1a6' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lccs_class</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-8c9796c6-e865-45a8-a6a3-62ae1b72823c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c9796c6-e865-45a8-a6a3-62ae1b72823c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66723957-dc87-4253-ad3d-57e4f6f2a574' class='xr-var-data-in' type='checkbox'><label for='data-66723957-dc87-4253-ad3d-57e4f6f2a574' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ancillary_variables :</span></dt><dd>processed_flag current_pixel_state observation_count change_count</dd><dt><span>flag_colors :</span></dt><dd>#ffff64 #ffff64 #ffff00 #aaf0f0 #dcf064 #c8c864 #006400 #00a000 #00a000 #aac800 #003c00 #003c00 #005000 #285000 #285000 #286400 #788200 #8ca000 #be9600 #966400 #966400 #966400 #ffb432 #ffdcd2 #ffebaf #ffc864 #ffd278 #ffebaf #00785a #009678 #00dc82 #c31400 #fff5d7 #dcdcdc #fff5d7 #0046c8 #ffffff</dd><dt><span>flag_meanings :</span></dt><dd>no_data cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban bare_areas bare_areas_consolidated bare_areas_unconsolidated water snow_and_ice</dd><dt><span>flag_values :</span></dt><dd>[0, 10, 11, 12, 20, 30, 40, 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100, 110, 120, 121, 122, 130, 140, 150, 151, 152, 153, 160, 170, 180, 190, 200, 201, 202, 210, 220]</dd><dt><span>long_name :</span></dt><dd>Land cover class defined in LCCS</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs</dd><dt><span>valid_max :</span></dt><dd>220</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.09 GiB </td>\n",
+       "                        <td> 15.26 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (5, 22225, 20223) </td>\n",
+       "                        <td> (1, 4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 180 chunks in 64 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"184\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"21\" x2=\"24\" y2=\"36\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"64\" x2=\"24\" y2=\"79\" />\n",
+       "  <line x1=\"10\" y1=\"86\" x2=\"24\" y2=\"101\" />\n",
+       "  <line x1=\"10\" y1=\"107\" x2=\"24\" y2=\"122\" />\n",
+       "  <line x1=\"10\" y1=\"120\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"122\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"125\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"128\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"131\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,134.9485979497544 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"119\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"122\" y2=\"2\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"125\" y2=\"5\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"128\" y2=\"8\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"131\" y2=\"11\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"134\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"46\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"74\" y1=\"0\" x2=\"89\" y2=\"14\" />\n",
+       "  <line x1=\"96\" y1=\"0\" x2=\"111\" y2=\"14\" />\n",
+       "  <line x1=\"117\" y1=\"0\" x2=\"132\" y2=\"14\" />\n",
+       "  <line x1=\"119\" y1=\"0\" x2=\"134\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 119.19055118110236,0.0 134.13914913085677,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"134\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"36\" x2=\"134\" y2=\"36\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"134\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"79\" x2=\"134\" y2=\"79\" />\n",
+       "  <line x1=\"24\" y1=\"101\" x2=\"134\" y2=\"101\" />\n",
+       "  <line x1=\"24\" y1=\"122\" x2=\"134\" y2=\"122\" />\n",
+       "  <line x1=\"24\" y1=\"134\" x2=\"134\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"46\" y1=\"14\" x2=\"46\" y2=\"134\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"134\" />\n",
+       "  <line x1=\"89\" y1=\"14\" x2=\"89\" y2=\"134\" />\n",
+       "  <line x1=\"111\" y1=\"14\" x2=\"111\" y2=\"134\" />\n",
+       "  <line x1=\"132\" y1=\"14\" x2=\"132\" y2=\"134\" />\n",
+       "  <line x1=\"134\" y1=\"14\" x2=\"134\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 134.13914913085677,14.948597949754403 134.13914913085677,134.9485979497544 24.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"79.543874\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20223</text>\n",
+       "  <text x=\"154.139149\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,154.139149,74.948598)\">22225</text>\n",
+       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">5</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e3a63e82-2b27-49ff-acda-b7287518d761' class='xr-section-summary-in' type='checkbox'  ><label for='section-e3a63e82-2b27-49ff-acda-b7287518d761' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-726ccd8c-291f-4a5e-8537-74dd71dda7af' class='xr-index-data-in' type='checkbox'/><label for='index-726ccd8c-291f-4a5e-8537-74dd71dda7af' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2018-01-01&#x27;, &#x27;2019-01-01&#x27;, &#x27;2020-01-01&#x27;, &#x27;2021-01-01&#x27;,\n",
+       "               &#x27;2022-01-01&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9a85852b-c4bf-4fd3-8a7b-4db902a3f5dc' class='xr-index-data-in' type='checkbox'/><label for='index-9a85852b-c4bf-4fd3-8a7b-4db902a3f5dc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1287677.0, 1287977.0, 1288277.0, 1288577.0, 1288877.0, 1289177.0,\n",
+       "       1289477.0, 1289777.0, 1290077.0, 1290377.0,\n",
+       "       ...\n",
+       "       7351577.0, 7351877.0, 7352177.0, 7352477.0, 7352777.0, 7353077.0,\n",
+       "       7353377.0, 7353677.0, 7353977.0, 7354277.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=20223))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b46a09cd-4ec4-41d7-af1c-b9b6403cc525' class='xr-index-data-in' type='checkbox'/><label for='index-b46a09cd-4ec4-41d7-af1c-b9b6403cc525' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([6906752.0, 6906452.0, 6906152.0, 6905852.0, 6905552.0, 6905252.0,\n",
+       "       6904952.0, 6904652.0, 6904352.0, 6904052.0,\n",
+       "       ...\n",
+       "        242252.0,  241952.0,  241652.0,  241352.0,  241052.0,  240752.0,\n",
+       "        240452.0,  240152.0,  239852.0,  239552.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=22225))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a158ba51-f3d8-4e9b-ba48-67e26db6caeb' class='xr-section-summary-in' type='checkbox'  ><label for='section-a158ba51-f3d8-4e9b-ba48-67e26db6caeb' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>TileSize :</span></dt><dd>2025:2025</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>https://www.ecmwf.int/en/about/contact-us/get-support</dd><dt><span>creation_date :</span></dt><dd>20181130T095451Z</dd><dt><span>creator_email :</span></dt><dd>landcover-cci@uclouvain.be</dd><dt><span>creator_name :</span></dt><dd>UCLouvain</dd><dt><span>creator_url :</span></dt><dd>http://www.uclouvain.be/</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>history :</span></dt><dd>amorgos-4,0, lc-sdr-1.0, lc-sr-1.0, lc-classification-1.0,lc-user-tools-3.13,lc-user-tools-4.3</dd><dt><span>id :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992-v2.0.7cds</dd><dt><span>institution :</span></dt><dd>UCLouvain</dd><dt><span>keywords :</span></dt><dd>land cover classification,satellite,observation</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>naming_authority :</span></dt><dd>org.esa-cci</dd><dt><span>product_version :</span></dt><dd>2.0.7cds</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-landcover-cci.org/</dd><dt><span>source :</span></dt><dd>MERIS FR L1B version 5.05, MERIS RR L1B version 8.0, SPOT VGT P</dd><dt><span>spatial_resolution :</span></dt><dd>300m</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Standard Names version 21</dd><dt><span>summary :</span></dt><dd>This dataset characterizes the land cover of a particular year (see time_coverage). The land cover was derived from the analysis of satellite data time series of the full period.</dd><dt><span>time_coverage_duration :</span></dt><dd>P1Y</dd><dt><span>time_coverage_end :</span></dt><dd>19921231</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1Y</dd><dt><span>time_coverage_start :</span></dt><dd>19920101</dd><dt><span>title :</span></dt><dd>Land Cover Map of ESA CCI brokered by CDS</dd><dt><span>tracking_id :</span></dt><dd>61b96fd7-42c3-4374-9de1-0dc3b0bcae2a</dd><dt><span>type :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:      (time: 5, x: 20223, y: 22225)\n",
+       "Coordinates:\n",
+       "  * time         (time) datetime64[ns] 40B 2018-01-01 2019-01-01 ... 2022-01-01\n",
+       "    spatial_ref  int64 8B 0\n",
+       "  * x            (x) float64 162kB 1.288e+06 1.288e+06 ... 7.354e+06 7.354e+06\n",
+       "  * y            (y) float64 178kB 6.907e+06 6.906e+06 ... 2.399e+05 2.396e+05\n",
+       "Data variables:\n",
+       "    lccs_class   (time, y, x) uint8 2GB dask.array<chunksize=(1, 4000, 4000), meta=np.ndarray>\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds_reproject = resample_in_space(ds, target_gm=target_gm)\n",
+    "ds_reproject"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "83dc5604-9139-4ad8-bc2d-78a3bc403ee4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2min 53s, sys: 46.9 s, total: 3min 40s\n",
+      "Wall time: 50.4 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x758df9d80050>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds_reproject.lccs_class.isel(time=-1)[::20, ::20].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "06e3efac-fe6d-45bd-abca-62590e8dd40c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 11.9 s, sys: 55.2 ms, total: 12 s\n",
+      "Wall time: 12 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
+       "Dimensions:      (time: 5, x: 20223, y: 22225)\n",
+       "Coordinates:\n",
+       "  * time         (time) datetime64[ns] 40B 2018-01-01 2019-01-01 ... 2022-01-01\n",
+       "    spatial_ref  int64 8B 0\n",
+       "  * x            (x) float64 162kB 1.288e+06 1.288e+06 ... 7.354e+06 7.354e+06\n",
+       "  * y            (y) float64 178kB 6.907e+06 6.906e+06 ... 2.399e+05 2.396e+05\n",
+       "Data variables:\n",
+       "    lccs_class   (time, y, x) uint8 2GB dask.array&lt;chunksize=(1, 4000, 4000), meta=np.ndarray&gt;\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9b7a6c88-5f7c-4819-8f02-827a1d910b05' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9b7a6c88-5f7c-4819-8f02-827a1d910b05' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>x</span>: 20223</li><li><span class='xr-has-index'>y</span>: 22225</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8e585e96-f022-4ed4-881f-d7b616c7d0a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8e585e96-f022-4ed4-881f-d7b616c7d0a6' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01 ... 2022-01-01</div><input id='attrs-06b3bf17-602b-4292-95d9-54b36b5c9d8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06b3bf17-602b-4292-95d9-54b36b5c9d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b1472ac-f51e-48f4-8717-e7b076807246' class='xr-var-data-in' type='checkbox'><label for='data-6b1472ac-f51e-48f4-8717-e7b076807246' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:00.000000000&#x27;, &#x27;2019-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-4133d162-fcd3-4ddd-88fd-93c12ccb1a2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4133d162-fcd3-4ddd-88fd-93c12ccb1a2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9e8d9ba-c277-4163-b5dc-346f6b4b22e3' class='xr-var-data-in' type='checkbox'><label for='data-b9e8d9ba-c277-4163-b5dc-346f6b4b22e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;ETRS89-extended / LAEA Europe&quot;,BASEGEOGCRS[&quot;ETRS89&quot;,ENSEMBLE[&quot;European Terrestrial Reference System 1989 ensemble&quot;,MEMBER[&quot;European Terrestrial Reference Frame 1989&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1990&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1991&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1992&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1993&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1994&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1996&quot;],MEMBER[&quot;European Terrestrial Reference Frame 1997&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2000&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2005&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2014&quot;],MEMBER[&quot;European Terrestrial Reference Frame 2020&quot;],ELLIPSOID[&quot;GRS 1980&quot;,6378137,298.257222101,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[0.1]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4258]],CONVERSION[&quot;Europe Equal Area 2001&quot;,METHOD[&quot;Lambert Azimuthal Equal Area&quot;,ID[&quot;EPSG&quot;,9820]],PARAMETER[&quot;Latitude of natural origin&quot;,52,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,10,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;False easting&quot;,4321000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,3210000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;northing (Y)&quot;,north,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;easting (X)&quot;,east,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Statistical analysis.&quot;],AREA[&quot;Europe - European Union (EU) countries and candidates. Europe - onshore and offshore: Albania; Andorra; Austria; Belgium; Bosnia and Herzegovina; Bulgaria; Croatia; Cyprus; Czechia; Denmark; Estonia; Faroe Islands; Finland; France; Germany; Gibraltar; Greece; Hungary; Iceland; Ireland; Italy; Kosovo; Latvia; Liechtenstein; Lithuania; Luxembourg; Malta; Monaco; Montenegro; Netherlands; North Macedonia; Norway including Svalbard and Jan Mayen; Poland; Portugal including Madeira and Azores; Romania; San Marino; Serbia; Slovakia; Slovenia; Spain including Canary Islands; Sweden; Switzerland; Türkiye (Turkey); United Kingdom (UK) including Channel Islands and Isle of Man; Vatican City State.&quot;],BBOX[24.6,-35.58,84.73,44.83]],ID[&quot;EPSG&quot;,3035]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314140356</dd><dt><span>inverse_flattening :</span></dt><dd>298.257222101</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>GRS 1980</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>ETRS89</dd><dt><span>horizontal_datum_name :</span></dt><dd>European Terrestrial Reference System 1989 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>ETRS89-extended / LAEA Europe</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>52.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>4321000.0</dd><dt><span>false_northing :</span></dt><dd>3210000.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.288e+06 1.288e+06 ... 7.354e+06</div><input id='attrs-1ec72bc9-e5f8-4cef-9747-c5aaa11e4681' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ec72bc9-e5f8-4cef-9747-c5aaa11e4681' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90156845-725f-4ee1-ab0d-d95164c65810' class='xr-var-data-in' type='checkbox'><label for='data-90156845-725f-4ee1-ab0d-d95164c65810' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1287677., 1287977., 1288277., ..., 7353677., 7353977., 7354277.],\n",
+       "      shape=(20223,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.907e+06 6.906e+06 ... 2.396e+05</div><input id='attrs-f9322e35-d2bb-4e64-9641-21090bcdc40f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9322e35-d2bb-4e64-9641-21090bcdc40f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-501524bc-c0d9-433d-bfab-ae0278f0279c' class='xr-var-data-in' type='checkbox'><label for='data-501524bc-c0d9-433d-bfab-ae0278f0279c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6906752., 6906452., 6906152., ...,  240152.,  239852.,  239552.],\n",
+       "      shape=(22225,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad17a8ab-d488-43c1-b5e4-e53638ef75e4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ad17a8ab-d488-43c1-b5e4-e53638ef75e4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lccs_class</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4000, 4000), meta=np.ndarray&gt;</div><input id='attrs-7068a511-6440-4930-8ee9-77f75971ec67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7068a511-6440-4930-8ee9-77f75971ec67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aabc7f56-c700-48ff-92ad-71871c0838a1' class='xr-var-data-in' type='checkbox'><label for='data-aabc7f56-c700-48ff-92ad-71871c0838a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ancillary_variables :</span></dt><dd>processed_flag current_pixel_state observation_count change_count</dd><dt><span>flag_colors :</span></dt><dd>#ffff64 #ffff64 #ffff00 #aaf0f0 #dcf064 #c8c864 #006400 #00a000 #00a000 #aac800 #003c00 #003c00 #005000 #285000 #285000 #286400 #788200 #8ca000 #be9600 #966400 #966400 #966400 #ffb432 #ffdcd2 #ffebaf #ffc864 #ffd278 #ffebaf #00785a #009678 #00dc82 #c31400 #fff5d7 #dcdcdc #fff5d7 #0046c8 #ffffff</dd><dt><span>flag_meanings :</span></dt><dd>no_data cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban bare_areas bare_areas_consolidated bare_areas_unconsolidated water snow_and_ice</dd><dt><span>flag_values :</span></dt><dd>[0, 10, 11, 12, 20, 30, 40, 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100, 110, 120, 121, 122, 130, 140, 150, 151, 152, 153, 160, 170, 180, 190, 200, 201, 202, 210, 220]</dd><dt><span>long_name :</span></dt><dd>Land cover class defined in LCCS</dd><dt><span>standard_name :</span></dt><dd>land_cover_lccs</dd><dt><span>valid_max :</span></dt><dd>220</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.09 GiB </td>\n",
+       "                        <td> 15.26 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (5, 22225, 20223) </td>\n",
+       "                        <td> (1, 4000, 4000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 180 chunks in 64 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> uint8 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"184\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"21\" x2=\"24\" y2=\"36\" />\n",
+       "  <line x1=\"10\" y1=\"43\" x2=\"24\" y2=\"58\" />\n",
+       "  <line x1=\"10\" y1=\"64\" x2=\"24\" y2=\"79\" />\n",
+       "  <line x1=\"10\" y1=\"86\" x2=\"24\" y2=\"101\" />\n",
+       "  <line x1=\"10\" y1=\"107\" x2=\"24\" y2=\"122\" />\n",
+       "  <line x1=\"10\" y1=\"120\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"122\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"125\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"128\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"131\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,134.9485979497544 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"119\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"122\" y2=\"2\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"125\" y2=\"5\" />\n",
+       "  <line x1=\"18\" y1=\"8\" x2=\"128\" y2=\"8\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"131\" y2=\"11\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"134\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"46\" y2=\"14\" />\n",
+       "  <line x1=\"53\" y1=\"0\" x2=\"68\" y2=\"14\" />\n",
+       "  <line x1=\"74\" y1=\"0\" x2=\"89\" y2=\"14\" />\n",
+       "  <line x1=\"96\" y1=\"0\" x2=\"111\" y2=\"14\" />\n",
+       "  <line x1=\"117\" y1=\"0\" x2=\"132\" y2=\"14\" />\n",
+       "  <line x1=\"119\" y1=\"0\" x2=\"134\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 119.19055118110236,0.0 134.13914913085677,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"134\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"36\" x2=\"134\" y2=\"36\" />\n",
+       "  <line x1=\"24\" y1=\"58\" x2=\"134\" y2=\"58\" />\n",
+       "  <line x1=\"24\" y1=\"79\" x2=\"134\" y2=\"79\" />\n",
+       "  <line x1=\"24\" y1=\"101\" x2=\"134\" y2=\"101\" />\n",
+       "  <line x1=\"24\" y1=\"122\" x2=\"134\" y2=\"122\" />\n",
+       "  <line x1=\"24\" y1=\"134\" x2=\"134\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"46\" y1=\"14\" x2=\"46\" y2=\"134\" />\n",
+       "  <line x1=\"68\" y1=\"14\" x2=\"68\" y2=\"134\" />\n",
+       "  <line x1=\"89\" y1=\"14\" x2=\"89\" y2=\"134\" />\n",
+       "  <line x1=\"111\" y1=\"14\" x2=\"111\" y2=\"134\" />\n",
+       "  <line x1=\"132\" y1=\"14\" x2=\"132\" y2=\"134\" />\n",
+       "  <line x1=\"134\" y1=\"14\" x2=\"134\" y2=\"134\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 134.13914913085677,14.948597949754403 134.13914913085677,134.9485979497544 24.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"79.543874\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20223</text>\n",
+       "  <text x=\"154.139149\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,154.139149,74.948598)\">22225</text>\n",
+       "  <text x=\"7.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,147.474299)\">5</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-44250b7f-4887-47bc-ab47-67dd98f90faf' class='xr-section-summary-in' type='checkbox'  ><label for='section-44250b7f-4887-47bc-ab47-67dd98f90faf' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d6f769ad-5c8e-461b-a09c-a7a09c7f95eb' class='xr-index-data-in' type='checkbox'/><label for='index-d6f769ad-5c8e-461b-a09c-a7a09c7f95eb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2018-01-01&#x27;, &#x27;2019-01-01&#x27;, &#x27;2020-01-01&#x27;, &#x27;2021-01-01&#x27;,\n",
+       "               &#x27;2022-01-01&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2b9777e7-b914-446d-9071-f8951090f37d' class='xr-index-data-in' type='checkbox'/><label for='index-2b9777e7-b914-446d-9071-f8951090f37d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1287677.0, 1287977.0, 1288277.0, 1288577.0, 1288877.0, 1289177.0,\n",
+       "       1289477.0, 1289777.0, 1290077.0, 1290377.0,\n",
+       "       ...\n",
+       "       7351577.0, 7351877.0, 7352177.0, 7352477.0, 7352777.0, 7353077.0,\n",
+       "       7353377.0, 7353677.0, 7353977.0, 7354277.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=20223))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-cfaf62d5-3557-49b6-93e9-32a8b11ae5aa' class='xr-index-data-in' type='checkbox'/><label for='index-cfaf62d5-3557-49b6-93e9-32a8b11ae5aa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([6906752.0, 6906452.0, 6906152.0, 6905852.0, 6905552.0, 6905252.0,\n",
+       "       6904952.0, 6904652.0, 6904352.0, 6904052.0,\n",
+       "       ...\n",
+       "        242252.0,  241952.0,  241652.0,  241352.0,  241052.0,  240752.0,\n",
+       "        240452.0,  240152.0,  239852.0,  239552.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=22225))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e1d7cf6-2841-43ec-8a10-3b2d210e36e8' class='xr-section-summary-in' type='checkbox'  ><label for='section-7e1d7cf6-2841-43ec-8a10-3b2d210e36e8' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>TileSize :</span></dt><dd>2025:2025</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>https://www.ecmwf.int/en/about/contact-us/get-support</dd><dt><span>creation_date :</span></dt><dd>20181130T095451Z</dd><dt><span>creator_email :</span></dt><dd>landcover-cci@uclouvain.be</dd><dt><span>creator_name :</span></dt><dd>UCLouvain</dd><dt><span>creator_url :</span></dt><dd>http://www.uclouvain.be/</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.002778</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>history :</span></dt><dd>amorgos-4,0, lc-sdr-1.0, lc-sr-1.0, lc-classification-1.0,lc-user-tools-3.13,lc-user-tools-4.3</dd><dt><span>id :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992-v2.0.7cds</dd><dt><span>institution :</span></dt><dd>UCLouvain</dd><dt><span>keywords :</span></dt><dd>land cover classification,satellite,observation</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>ESA CCI Data Policy: free and open access</dd><dt><span>naming_authority :</span></dt><dd>org.esa-cci</dd><dt><span>product_version :</span></dt><dd>2.0.7cds</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-landcover-cci.org/</dd><dt><span>source :</span></dt><dd>MERIS FR L1B version 5.05, MERIS RR L1B version 8.0, SPOT VGT P</dd><dt><span>spatial_resolution :</span></dt><dd>300m</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Standard Names version 21</dd><dt><span>summary :</span></dt><dd>This dataset characterizes the land cover of a particular year (see time_coverage). The land cover was derived from the analysis of satellite data time series of the full period.</dd><dt><span>time_coverage_duration :</span></dt><dd>P1Y</dd><dt><span>time_coverage_end :</span></dt><dd>19921231</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1Y</dd><dt><span>time_coverage_start :</span></dt><dd>19920101</dd><dt><span>title :</span></dt><dd>Land Cover Map of ESA CCI brokered by CDS</dd><dt><span>tracking_id :</span></dt><dd>61b96fd7-42c3-4374-9de1-0dc3b0bcae2a</dd><dt><span>type :</span></dt><dd>ESACCI-LC-L4-LCCS-Map-300m-P1Y</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:      (time: 5, x: 20223, y: 22225)\n",
+       "Coordinates:\n",
+       "  * time         (time) datetime64[ns] 40B 2018-01-01 2019-01-01 ... 2022-01-01\n",
+       "    spatial_ref  int64 8B 0\n",
+       "  * x            (x) float64 162kB 1.288e+06 1.288e+06 ... 7.354e+06 7.354e+06\n",
+       "  * y            (y) float64 178kB 6.907e+06 6.906e+06 ... 2.399e+05 2.396e+05\n",
+       "Data variables:\n",
+       "    lccs_class   (time, y, x) uint8 2GB dask.array<chunksize=(1, 4000, 4000), meta=np.ndarray>\n",
+       "Attributes: (12/38)\n",
+       "    Conventions:                CF-1.6\n",
+       "    TileSize:                   2025:2025\n",
+       "    cdm_data_type:              grid\n",
+       "    comment:                    \n",
+       "    contact:                    https://www.ecmwf.int/en/about/contact-us/get...\n",
+       "    creation_date:              20181130T095451Z\n",
+       "    ...                         ...\n",
+       "    time_coverage_end:          19921231\n",
+       "    time_coverage_resolution:   P1Y\n",
+       "    time_coverage_start:        19920101\n",
+       "    title:                      Land Cover Map of ESA CCI brokered by CDS\n",
+       "    tracking_id:                61b96fd7-42c3-4374-9de1-0dc3b0bcae2a\n",
+       "    type:                       ESACCI-LC-L4-LCCS-Map-300m-P1Y"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds_clip = ds.sel(lon=slice(-20, 40), lat=slice(85, 25))\n",
+    "ds_clip_reproject = resample_in_space(ds_clip, target_gm=target_gm)\n",
+    "ds_clip_reproject"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "22ac18ef-8061-410e-a0e0-9ec663f1d306",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 3min 1s, sys: 56.1 s, total: 3min 57s\n",
+      "Wall time: 27.1 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x758d913c6ad0>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds_clip_reproject.lccs_class.isel(time=-1)[::20, ::20].plot()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/guide.md b/docs/guide.md
new file mode 100644
index 0000000..4ab158d
--- /dev/null
+++ b/docs/guide.md
@@ -0,0 +1,299 @@
+# User Guide for xcube-resampling
+
+**xcube-resampling** provides algorithms for up- and downsampling
+a gridded dataset in both spatial grids and temporal scales.
+It supports:
+
+- **[Spatial]** Simple resampling via affine transformation  
+- **[Spatial]** Reprojection between coordinate reference systems (CRS)  
+- **[Spatial]** Rectification of non-regular grids to regular grids  
+- **[Temporal]** Up- and Downsampling in the time dimension to the frequency and method requested.
+
+All spatial resampling methods are built around the [`GridMapping`](api.md/#xcube_resampling.gridmapping.GridMapping)
+class, which represents a spatial grid mapping and contains all necessary information
+for resampling.  
+
+We first introduce the `GridMapping` class before explaining the three spatial resampling
+algorithms.
+
+---
+
+## `GridMapping` – the grid mapping object
+
+A `GridMapping` defines the spatial structure of a dataset. It follows the 
+[CF conventions for grid mappings](https://cfconventions.org/Data/cf-conventions/cf-conventions-1.12/cf-conventions.html#grid-mappings-and-projections) 
+and provides a standardized way to describe geospatial grids. It stores metadata such
+as the coordinate reference system (CRS), spatial resolution, bounding box, spatial
+dimensions, coordinates, and tile size (for chunked datasets).
+
+Grids can be defined in two ways:
+
+- **1D coordinates** – regular grids defined by evenly spaced x/y or lat/lon axes.  
+- **2D coordinates** – irregular grids where each pixel has its own pair of x/y or 
+  lat/lon coordinates.
+
+### Creating a `GridMapping` object
+
+There are three main ways to create a `GridMapping` instance:
+
+#### 1. Regular grid mapping
+
+Use [`GridMapping.regular`](api.md/#xcube_resampling.gridmapping.GridMapping.regular):
+
+```python
+from xcube_resampling.gridmapping import GridMapping
+
+gm = GridMapping.regular(size, xy_min, xy_res, crs)
+```
+
+Parameter descriptions can be found [here](api.md/#xcube_resampling.gridmapping.GridMapping.regular).
+
+#### 2. Create a grid mapping from an existing dataset
+
+Use the [`GridMapping.from_dataset`](api.md/#xcube_resampling.gridmapping.GridMapping.from_dataset)
+method:
+
+```python
+from xcube_resampling.gridmapping import GridMapping
+
+gm = GridMapping.from_dataset(ds)
+```
+Here, `ds` is a `xarray.Dataset`. Further optional parameters can be found [here](api.md/#xcube_resampling.gridmapping.GridMapping.from_dataset).
+> **Note:** If no grid mapping is provided for the input dataset, the resampling functions 
+> use this method to derive one.
+
+#### 3. Create a grid mapping from coordinates 
+Use the [`GridMapping.from_coords`](api.md/#xcube_resampling.gridmapping.GridMapping.from_coords)
+method:
+
+```python
+from xcube_resampling.gridmapping import GridMapping
+
+gm = GridMapping.from_coords(x_coords, y_coords, crs)
+```
+Here, `x_coords` and `y_coords` are `xarray.Array` instances, and `crs` is the 
+coordinate reference system (CRS). Further details of the parameters can be found
+[here](api.md/#xcube_resampling.gridmapping.GridMapping.from_dataset).
+
+#### Derive new `GridMapping` instances
+
+You can create new grid mappings from existing ones using:
+
+- [derive](api.md/#xcube_resampling.gridmapping.GridMapping.derive): 
+  change selected properties.
+- [scale](api.md/#xcube_resampling.gridmapping.GridMapping.scale): 
+  create a scaled version of a regular grid mapping.
+- [to_regular](api.md/#xcube_resampling.gridmapping.GridMapping.derive):
+  convert an irregular grid mapping to a regular one.
+- [transform](api.md/#xcube_resampling.gridmapping.GridMapping.transform):
+  change the CRS of a grid mapping (regular → irregular with 2D coordinates).
+
+An example is available in the [Example Notebooks](examples/coords.ipynb).
+
+---
+
+### Spatial Resampling Algorithms
+
+The function [`resample_in_space`](api.md/#xcube_resampling.resample_in_space)
+integrates all three resampling algorithms and automatically selects the most
+appropriate one:
+
+| Algorithm             | Function                                                                                                                      | Selection Criteria                                                                                   |
+|-----------------------|-------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------|
+| **Affine Transformation** | [`affine_transform_dataset`](api.md/#xcube_resampling.affine_transform_dataset) | Source and target grids are both regular and share the same CRS.                                    |
+| **Reprojection**      | [`reproject_dataset`](api.md/#xcube_resampling.reproject_dataset)         | Source and target grids are both regular but have different CRS.                                  |
+| **Rectification**     | [`rectify_dataset`](api.md/#xcube_resampling.rectify_dataset)               | 	Source grid is irregular with 2D coordinates.                                            |
+
+With `resample_in_space`, users do **not** need to worry about selecting the right
+algorithm—the function determines and applies it automatically.
+
+#### Common parameters for all resampling algorithms
+
+| Parameter       | Type / Accepted Values | Description | Default                                                                     |
+|-----------------|------------------------|-------------|-----------------------------------------------------------------------------|
+| `variables`     | `str` or iterable of `str` | Name(s) of variables to resample. If `None`, all data variables are processed. | `None`                                                                      |
+| `interp_methods`| `int`, `str`, or `dict` mapping var/dtype to method. Supported:<br>• `0` — nearest neighbor<br>• `1` — linear / bilinear<br>• `"nearest"`<br>• `"triangular"`<br>• `"bilinear"` | Interpolation method for upsampling spatial data variables. Can be a single value or per-variable/dtype mapping. | `0` for integer arrays, else `1`                                            |
+| `agg_methods`   | `str` or `dict` mapping var/dtype to method. Supported:<br>`"center"`, `"count"`, `"first"`, `"last"`, `"max"`, `"mean"`, `"median"`, `"mode"`, `"min"`, `"prod"`, `"std"`, `"sum"`, `"var"` | Aggregation method for downsampling spatial data variables. | `"center"` for integer arrays, else `"mean"`                                |
+| `prevent_nan_propagation`  | `bool` or `dict` mapping var/dtype to `bool` | Prevents NaN propagation during upsampling (only applies when interpolation method is not nearest). | `False`                                                                     |
+| `fill_values`   | scalar or `dict` mapping var/dtype to value. | Fill value(s) for areas outside input coverage. | <br>• float — NaN<br>• uint8 — 255<br>• uint16 — 65535<br>• other ints — -1 |
+
+
+
+#### 1. Affine Transformation
+
+An **affine transformation** can be applied when both the source and target grid
+mappings are **regular** and share the same CRS. The function
+[`affine_transform_dataset`](api.md/#xcube_resampling.affine_transform_dataset)
+requires the input dataset and the target grid mapping.  
+
+For any data array in the dataset with **two spatial dimensions as the last two axes**,
+an affine transformation is performed using
+[`dask_image.ndinterp.affine_transform`](https://image.dask.org/en/latest/dask_image.ndinterp.html).
+The resulting dataset contains resampled data arrays aligned to the target grid mapping.  
+
+- Data variables **without spatial dimensions** are copied to the output.  
+- Variables with **only one spatial dimension** are ignored.  
+
+> **Note:** The `interp_methods` parameter corresponds to the `order` parameter in
+> [`dask_image.ndinterp.affine_transform`](https://image.dask.org/en/latest/dask_image.ndinterp.html).
+> Only spline orders `[0, 1]` are supported to avoid unintended blending across
+> non-spatial dimensions (e.g., time) in 3D arrays.  
+
+Simple examples of affine transformations are shown in the
+[Example Notebook Affine Transformation](examples/affine.ipynb).
+
+---
+
+#### 2. Reprojection
+
+**Reprojection** can be applied when both source and target grid mappings are
+**regular** but use **different CRSs**. The function
+[`reproject_dataset`](api.md/#xcube_resampling.reproject_dataset)
+requires the input dataset and the target grid mapping.  
+
+The procedure is as follows:
+
+1. Check if the **target grid resolution** is coarser than the source grid resolution.
+   If so, the source dataset is **downsampled/aggregated** using affine resampling.  
+2. Transform the **target coordinates** to the source CRS, producing **2D irregular
+   coordinates**.  
+3. For each transformed irregular pixel location, identify **sub-pixel values** in
+   the regular source grid.  
+4. Perform the selected **interpolation** using these sub-pixel values.  
+
+Supported interpolation methods are described in [Section Interpolation Methods](#interpolation-methods).  
+
+A large-scale example is shown in the
+[Example Notebooks](examples/resample_in_space_large_example_reproject_dataset.ipynb).
+
+---
+
+#### 3. Rectification
+
+**Rectification** is used when the source dataset has an **irregular grid**. The
+function [`rectify_dataset`](api.md/#xcube_resampling.rectify_dataset)
+requires only the input dataset.  
+
+If no target grid mapping is provided, the source grid mapping is **converted to a
+regular grid**, and interpolation is performed so that the new dataset is defined on
+this regular grid.  
+
+The procedure is as follows:
+
+1. If the **CRS differs**, the 2D irregular source grid is transformed to the target
+   CRS, resulting in 2D coordinates in the target CRS.  
+2. If the **target resolution** is coarser than the source resolution, the source
+   dataset is **downsampled/aggregated** using affine resampling.  
+3. For each regular target grid point, determine the **sub-pixel position** in the
+   irregular (optionally transformed) source grid.  
+
+> **Note:** Determining sub-pixel positions in an irregular grid is more
+> **computationally expensive** than the reprojection algorithm, as the lookup grid is
+> irregular. These positions determine the **neighboring points** used for the selected
+> interpolation method.  
+
+Supported interpolation methods are described in [Section Interpolation Methods](#interpolation-methods).  
+
+An example notebook demonstrating Sentinel-3 scene rectification is available in the
+[Example Notebooks](examples/rectify_sentinel3.ipynb).
+
+### Interpolation Methods
+
+As mentioned in [Section Reprojection](#2-reprojection) and
+[Section Rectification](#3-rectification), two 2D coordinate images are generated,
+showing the subpixel fractions *u, v* of a target point with respect to the source
+grid points, as depicted in the following image:
+
+![Algorithm #2](images/algo-1.png)
+
+This is the starting point for all three interpolation methods described below.
+
+#### Nearest Neighbor - `"nearest"`, `0`
+
+The simplest case is a **nearest neighbor lookup**, which determines the pixel value *V*
+of point *P* in the target grid mapping according to:
+
+- *V = V1 if u <= ½ and v <= ½*  
+- *V = V2 if u > ½ and v <= ½*  
+- *V = V3 if u <= ½ and v > ½*  
+- *V = V4 if u > ½ and v > ½*  
+
+where *V1*, *V2*, *V3*, *V4* are the pixel values of the corresponding points in the
+source dataset.  
+
+The interpolation is shown in the following image:
+
+![Algorithm #3](images/algo-3.png)
+
+#### Bilinear - `"bilinear"`, `1`
+
+**Bilinear interpolation** uses the four adjacent source pixels to compute the value
+*V* of point *P* in the target grid mapping according to:
+
+*V = VA + v (VB − VA)*  
+
+with  
+
+*VA = V1 + u (V2 − V1)*  
+*VB = V3 + u (V4 − V3)*  
+
+where *V1*, *V2*, *V3*, *V4* are the pixel values of the corresponding points in the
+source dataset.
+
+#### Triangular - `"triangular"`
+
+The triangluar interpolation can be used to speed up the bilinear interpolation. It 
+uses three adjacent source pixels to determine the pixel value *V* of point *P* in 
+the target grid mapping according to:
+
+- *V = V1 + u (V2 − V1) + v (V3 − V1), if u+v < 1*  
+- *V = V4 + (1 - u) (V3 − V4) + (1 - v) (V2 − V4), if u+v >= 1*  
+
+where *V1*, *V2*, *V3*, *V4* are the pixel values of the points in the source dataset.
+
+#### Remarks
+
+1. If the **target pixel size is much smaller** than the source pixel size, and the
+   source has low spatial resolution, results may be inaccurate. Curved source pixel
+   boundaries must be considered for many projections.
+2. If *x, y* are decimal longitude and latitude, and the north or south poles are in
+   the scene, the algorithm may fail. Workarounds include:
+    * Transforming source coordinates into another suitable CRS first.  
+    * Transforming longitude values *x* into complex numbers and normalizing latitudes
+      *y* to the range [-1, +1]:  
+
+            x' = cos(x) + i sin(x)  
+            y' = 2y / π
+
+---
+
+#### Interpolation
+
+When interpolation is required,
+[`xarray.core.resample.DataArrayResample.interpolate`](https://docs.xarray.dev/en/v2024.05.0/generated/xarray.core.resample.DataArray.Resample.interpolate.html)
+is used internally.
+
+Available interpolation methods defined in
+[`TemporalInterpMethod`](api.md/#xcube_resampling.constants.TemporalInterpMethod) and
+ correspond to the `kind` argument in
+[`xarray.core.resample.DataArrayResample.interpolate`](https://docs.xarray.dev/en/v2024.05.0/generated/xarray.core.resample.DataArrayResample.interpolate.html).
+
+**Defaults:**
+
+- `nearest` for integer data
+- `linear` for all other data types
+
+
+#### Aggregation
+
+When aggregation is applied, the available aggregation methods are defined in
+[`TemporalAggMethod`](api.md/#xcube_resampling.constants.TemporalAggMethod).
+
+Refer to the
+[`xarray.core.resample.DataArrayResample`](https://docs.xarray.dev/en/v2024.05.0/generated/xarray.core.resample.DataArray.Resample.html)
+documentation for detailed descriptions of supported aggregation operations.
+
+**Defaults:**
+
+- `nearest` for integer data
+- `mean` for all other data types
diff --git a/docs/images/algo-1.png b/docs/images/algo-1.png
new file mode 100644
index 0000000..47efc14
Binary files /dev/null and b/docs/images/algo-1.png differ
diff --git a/docs/images/algo-2.png b/docs/images/algo-2.png
new file mode 100644
index 0000000..a1756dc
Binary files /dev/null and b/docs/images/algo-2.png differ
diff --git a/docs/images/algo-3.png b/docs/images/algo-3.png
new file mode 100644
index 0000000..d202495
Binary files /dev/null and b/docs/images/algo-3.png differ
diff --git a/docs/images/olci-input.png b/docs/images/olci-input.png
new file mode 100644
index 0000000..1d3ff3d
Binary files /dev/null and b/docs/images/olci-input.png differ
diff --git a/docs/images/olci-output.png b/docs/images/olci-output.png
new file mode 100644
index 0000000..01ddfaa
Binary files /dev/null and b/docs/images/olci-output.png differ
diff --git a/docs/images/solve-bilinear.png b/docs/images/solve-bilinear.png
new file mode 100644
index 0000000..3c97326
Binary files /dev/null and b/docs/images/solve-bilinear.png differ
diff --git a/docs/images/source-coords.png b/docs/images/source-coords.png
new file mode 100644
index 0000000..e78f235
Binary files /dev/null and b/docs/images/source-coords.png differ
diff --git a/docs/index.md b/docs/index.md
new file mode 100644
index 0000000..cb6c3fd
--- /dev/null
+++ b/docs/index.md
@@ -0,0 +1,62 @@
+# xcube-resampling
+
+**xcube-resampling** provides efficient algorithms for transforming datasets into 
+different spatial grids and temporal scales. It is designed for geospatial workflows that need 
+flexible resampling and reprojection. This library provides up and downsampling for both 
+spatial and temporal domains.
+
+### ✨ Features
+- #### Spatial Resampling
+    - **Affine resampling** – simple resampling using affine transformations  
+    - **Reprojection** – convert datasets between different coordinate reference systems (CRS)  
+    - **Rectification** – transform irregular grids into regular, well-structured grids  
+
+- #### Temporal Resampling
+    - **Time-based resampling** – upsample or downsample data along the time dimension
+
+All methods work seamlessly with chunked (lazily loaded) [xarray.Datasets](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html) and are powered by [Dask](https://www.dask.org/) for scalable, out-of-core computation.
+
+### ⚡ Lightweight & Independent
+The package is independent of the core *xcube* framework and has minimal dependencies:
+`affine, dask, dask-image, numba, numpy, pyproj, xarray, zarr`.
+
+
+## Overview
+
+The spatial resampling methods are built around the
+[`GridMapping`](api.md/#xcube_resampling.gridmapping.GridMapping)
+class, which represents a spatial grid mapping and contains all necessary information
+for resampling.  
+
+A `GridMapping` is required for affine transformation and reprojection, and optional
+for rectification. If omitted for rectification, a simple rectification will be
+performed while staying in the same CRS.
+
+The temporal resampling method is built around the [`Resampler`](https://docs.xarray.dev/en/stable/generated/xarray.groupers.Resampler.html#xarray.groupers.Resampler)
+class, which provides methods to up or downsample a temporal dataset
+into the requested frequency.
+---
+
+### `resample_in_space` — the gateway to Spatial Resampling of Gridded datasets
+
+The **central function** for spatial up and down resampling is
+[`resample_in_space`](api.md/#xcube_resampling.resample_in_space), which integrates all
+three algorithms and **automatically selects** the appropriate one based on the
+criteria below.
+
+| Algorithm             | Function                                                                               | Selection Criteria                                                                                   |
+|-----------------------|----------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------|
+| **Affine Transformation** | [`affine_transform_dataset`](api.md/#xcube_resampling.affine.affine_transform_dataset) | Source and target grids are both regular and share the same CRS.                                    |
+| **Reprojection**      | [`reproject_dataset`](api.md/#xcube_resampling.reproject.reproject_dataset)            | Source and target grids are both regular but have different CRS.                                    |
+| **Rectification**     | [`rectify_dataset`](api.md/#xcube_resampling.rectify.rectify_dataset)                  | Source grid is irregular and contains 2D coordinates.                                               |
+
+With `resample_in_space`, users do **not** need to worry about selecting the right
+algorithm—the function determines and applies it automatically.
+
+
+## License
+
+`xcube-resampling` is open source made available under the terms and conditions of the 
+[MIT license](https://opensource.org/license/mit).
+
+`
\ No newline at end of file
diff --git a/docs/start.md b/docs/start.md
new file mode 100644
index 0000000..48072a8
--- /dev/null
+++ b/docs/start.md
@@ -0,0 +1,77 @@
+# Getting Started
+
+The `xcube-resampling` package can be installed into an existing Python environment
+using
+
+```bash
+pip install xcube-resampling
+```
+
+or
+
+```bash
+conda install -c conda-forge xcube-resampling
+```
+
+After installation, you are ready to go and use `resample_in_space` to resample you
+datasets: 
+
+### Generate a sample dataset
+
+```python
+import numpy as np
+import xarray as xr
+
+res = 0.1
+source_ds = xr.Dataset(
+    data_vars=dict(
+        refl=xr.DataArray(
+            np.array(
+                [
+                    [0, 1, 0, 2, 0, 3, 0, 4],
+                    [2, 0, 3, 0, 4, 0, 1, 0],
+                    [0, 4, 0, 1, 0, 2, 0, 3],
+                    [1, 0, 2, 0, 3, 0, 4, 0],
+                    [0, 3, 0, 4, 0, 1, 0, 2],
+                    [4, 0, 1, 0, 2, 0, 3, 0],
+                ],
+                dtype=np.float64,
+            ),
+            dims=("lat", "lon"),
+        )
+    ),
+    coords=dict(
+        lon=xr.DataArray(50.0 + res * np.arange(0, 8) + 0.5 * res, dims="lon"),
+        lat=xr.DataArray(10.6 - res * np.arange(0, 6) - 0.5 * res, dims="lat"),
+    ),
+)
+```
+
+### Apply resampling
+
+```python
+from xcube_resampling.spatial import resample_in_space
+from xcube_resampling.gridmapping import GridMapping
+
+target_gm = GridMapping.regular((3, 3), (50.05, 10.05), 0.2, "EPSG:4326")
+target_ds = resample_in_space(source_ds, target_gm=target_gm)
+```
+
+
+The resulting dataset `target_ds` has a size of 3×3, as defined by the target 
+grid mapping:
+
+```text
+<xarray.Dataset> Size: 128B
+Dimensions:      (lat: 3, lon: 3)
+Coordinates:
+    spatial_ref  int64 8B 0
+  * lon          (lon) float64 24B 50.15 50.35 50.55
+  * lat          (lat) float64 24B 10.55 10.35 10.15
+Data variables:
+    refl         (lat, lon) float64 72B 0.875 1.375 1.375 1.5 ... 1.25 1.5 1.0
+
+```
+
+For more examples, including visualization, please refer to the
+[Example Notebooks](examples/affine.ipynb).
diff --git a/docs/stylesheets/xarray_dataset.css b/docs/stylesheets/xarray_dataset.css
new file mode 100644
index 0000000..3dd6ffa
--- /dev/null
+++ b/docs/stylesheets/xarray_dataset.css
@@ -0,0 +1,35 @@
+.md-typeset pre.xr-text-repr-fallback {
+    display: none;
+}
+
+.md-typeset ul.xr-sections, .jupyter-wrapper .jp-OutputArea-output dl.xr-attrs {
+    display: grid;
+}
+
+.md-typeset li.xr-var-item, .md-typeset ul.xr-var-list {
+    display: contents;
+}
+
+.md-typeset .xr-section-details {
+    display: none;
+}
+
+.md-typeset ul.xr-dim-list li {
+    margin-bottom: 0;
+    margin-left: 0;
+}
+
+.md-typeset ul.xr-dim-list {
+    margin-bottom: 0;
+    margin-top: 0;
+}
+
+.jupyter-wrapper .jp-OutputArea-output .xr-attrs dt {
+    padding: 0;
+    margin: 0;
+    float: left;
+    padding-right: 10px;
+    width: auto;
+    font-weight: normal;
+    grid-column: 1;
+}
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
new file mode 100644
index 0000000..da1d343
--- /dev/null
+++ b/mkdocs.yml
@@ -0,0 +1,70 @@
+site_name: xcube-resampling
+repo_url: https://github.com/xcube-dev/xcube-resampling
+repo_name: xcube-dev/xcube-resampling
+
+copyright: Copyright &copy; 2025 Brockmann Consult
+
+nav:
+  - Overview: index.md
+  - Getting Started: start.md
+  - User Guide: guide.md
+  - Example Notebooks:
+      - GridMapping instance: examples/coords.ipynb
+      - Affine Transformation: examples/affine.ipynb
+      - Rectification of a Sentinel-3 tile: examples/rectify_sentinel3.ipynb
+      - Reprojection of large Land Cover Map: examples/resample_in_space_large_example_reproject_dataset.ipynb
+  - Python API: api.md
+  - About: about.md
+
+theme:
+  name: material
+  # logo: assets/logo.png
+  # favicon: assets/logo-small.png
+  palette:
+    # Palette toggle for light mode
+    - scheme: default
+      primary: blue grey
+      toggle:
+        icon: material/brightness-7
+        name: Switch to dark mode
+    # Palette toggle for dark mode
+    - scheme: slate
+      primary: blue grey
+      toggle:
+        icon: material/brightness-4
+        name: Switch to light mode
+
+markdown_extensions:
+  - attr_list
+  - admonition
+  - pymdownx.details
+  - pymdownx.superfences
+  - pymdownx.emoji:
+      emoji_index: !!python/name:material.extensions.emoji.twemoji
+      emoji_generator: !!python/name:material.extensions.emoji.to_svg
+
+extra:
+  social:
+    - icon: fontawesome/brands/github
+      link: https://github.com/xcube-dev/xcube-resampling
+    #- icon: fontawesome/brands/python
+    #  link: https://pypi.org/project/xcube-resampling/
+
+extra_css:
+  - stylesheets/xarray_dataset.css
+
+plugins:
+  - search
+  - mkdocs-jupyter
+  - autorefs
+  - mkdocstrings:
+      handlers:
+        python:
+          options:
+            docstring_style: google
+            show_root_toc_entry: true
+            show_root_heading: true
+            show_source: true
+            heading_level: 2
+            annotations_path: brief
+            members_order: source