datasets/io-lulc/io-lulc-example.ipynb

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    "## Accessing Esri 10m Land Use/Land Cover data with the Planetary Computer STAC API\n",
    "\n",
    "This dataset contains global estimates of 10-class land use/land cover for 2020, derived from ESA Sentinel-2 imagery at 10m resolution. In this notebook, we'll demonstrate how to access and work with this data through the Planetary Computer."
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    "### Environment setup\n",
    "\n",
    "This notebook works with or without an API key, but you will be given more permissive access to the data with an API key.\n",
    "The [Planetary Computer Hub](https://planetarycomputer.microsoft.com/compute) is pre-configured to use your API key."
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    "from dask.distributed import Client as dask_client\n",
    "from matplotlib.colors import ListedColormap\n",
    "from pystac_client import Client\n",
    "from pystac.extensions.raster import RasterExtension as raster\n",
    "from pystac.extensions.projection import ProjectionExtension as proj\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import planetary_computer as pc\n",
    "import rasterio\n",
    "import rasterio.features\n",
    "import stackstac\n",
    "\n",
    "# Set the environment variable PC_SDK_SUBSCRIPTION_KEY, or set it here.\n",
    "# The Hub sets PC_SDK_SUBSCRIPTION_KEY automatically.\n",
    "# pc.settings.set_subscription_key(<YOUR API Key>)"
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    "### Select a region and find data items\n",
    "\n",
    "We'll pick an area surrounding Manila, Philippines and use the STAC API to find what data items are avaialable. We won't select a date range since this dataset contains items from a single timeframe in 2020."
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    "area_of_interest = {\n",
    "    \"type\": \"Polygon\",\n",
    "    \"coordinates\": [\n",
    "        [\n",
    "            [120.88256835937499, 14.466596475463248],\n",
    "            [121.34948730468749, 14.466596475463248],\n",
    "            [121.34948730468749, 14.81737062015525],\n",
    "            [120.88256835937499, 14.817370620155254],\n",
    "            [120.88256835937499, 14.466596475463248],\n",
    "        ]\n",
    "    ],\n",
    "}"
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     "text": [
      "Returned 4 Items\n"
     ]
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   "source": [
    "catalog = Client.open(\"https://planetarycomputer.microsoft.com/api/stac/v1\")\n",
    "\n",
    "search = catalog.search(collections=[\"io-lulc\"], intersects=area_of_interest)\n",
    "\n",
    "# Check how many items were returned\n",
    "items = list(search.get_items())\n",
    "print(f\"Returned {len(items)} Items\")"
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    "We found 4 items that intersect with our area of interest, which means the data we want to work with is spread out over 4 non-overlapping GeoTIFF files stored on blob storage. In order to merge them together, we could open each item, clip to the subset of our AoI, and merge them together manually with rasterio. We'd also have to reproject each item which may span multiple UTM projections. \n",
    "\n",
    "Instead, we'll use the [stackstac](https://stackstac.readthedocs.io/en/latest/) library to read, merge, and reproject in a single step - all without loading the rest of the file data we don't need."
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       "    resolution:  10.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'stackstac-c32fed696ee8899b67549452eb38099a'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 3924</li><li><span class='xr-has-index'>x</span>: 5063</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9b69bee9-a54a-466b-8524-b8dcfd89fd06' class='xr-array-in' type='checkbox' checked><label for='section-9b69bee9-a54a-466b-8524-b8dcfd89fd06' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 1024, 1024), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "\n",
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       "  <text x=\"12.706308\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
       "  <text x=\"45.412617\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,45.412617,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "  <line x1=\"95\" y1=\"48\" x2=\"109\" y2=\"63\" />\n",
       "  <line x1=\"95\" y1=\"72\" x2=\"109\" y2=\"87\" />\n",
       "  <line x1=\"95\" y1=\"93\" x2=\"109\" y2=\"107\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"95\" y1=\"0\" x2=\"95\" y2=\"93\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"109\" y1=\"14\" x2=\"109\" y2=\"107\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"95.0,0.0 109.9485979497544,14.948597949754403 109.9485979497544,107.95274568824935 95.0,93.00414773849495\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"95\" y1=\"0\" x2=\"215\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "  <!-- Vertical lines -->\n",
       "  <line x1=\"95\" y1=\"0\" x2=\"109\" y2=\"14\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"192\" y1=\"0\" x2=\"207\" y2=\"14\" />\n",
       "  <line x1=\"215\" y1=\"0\" x2=\"229\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"95.0,0.0 215.0,0.0 229.9485979497544,14.948597949754403 109.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"109\" y1=\"14\" x2=\"229\" y2=\"14\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"109\" y1=\"14\" x2=\"109\" y2=\"107\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"134\" y1=\"14\" x2=\"134\" y2=\"107\" />\n",
       "  <line x1=\"158\" y1=\"14\" x2=\"158\" y2=\"107\" />\n",
       "  <line x1=\"182\" y1=\"14\" x2=\"182\" y2=\"107\" />\n",
       "  <line x1=\"207\" y1=\"14\" x2=\"207\" y2=\"107\" />\n",
       "  <line x1=\"229\" y1=\"14\" x2=\"229\" y2=\"107\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"109.9485979497544,14.948597949754403 229.9485979497544,14.948597949754403 229.9485979497544,107.95274568824935 109.9485979497544,107.95274568824935\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
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       "  <text x=\"169.948598\" y=\"127.952746\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >5063</text>\n",
       "  <text x=\"249.948598\" y=\"61.450672\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,249.948598,61.450672)\">3924</text>\n",
       "  <text x=\"92.474299\" y=\"120.478447\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,92.474299,120.478447)\">1</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-ca3ecbd1-4fb2-408b-8a05-a6868f6d712b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca3ecbd1-4fb2-408b-8a05-a6868f6d712b' class='xr-section-summary' >Coordinates: <span>(17)</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'>2020-06-01</div><input id='attrs-e41bbf17-4835-46b3-8368-fdb6854f0904' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e41bbf17-4835-46b3-8368-fdb6854f0904' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dce54735-5a8e-4890-b8eb-d514506ce4b0' class='xr-var-data-in' type='checkbox'><label for='data-dce54735-5a8e-4890-b8eb-d514506ce4b0' 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([&#x27;2020-06-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;51P-2020&#x27;</div><input id='attrs-aceeccdb-3108-42b9-bf6d-db99233d4550' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aceeccdb-3108-42b9-bf6d-db99233d4550' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26093c4b-bf74-4d76-8b0e-e6d3e98f4040' class='xr-var-data-in' type='checkbox'><label for='data-26093c4b-bf74-4d76-8b0e-e6d3e98f4040' 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([&#x27;51P-2020&#x27;], dtype=&#x27;&lt;U8&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;data&#x27;</div><input id='attrs-8bebaed6-2663-4e0a-98df-083580f6fc78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8bebaed6-2663-4e0a-98df-083580f6fc78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3da48678-2d7f-46c4-97c5-d773c710b4f0' class='xr-var-data-in' type='checkbox'><label for='data-3da48678-2d7f-46c4-97c5-d773c710b4f0' 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([&#x27;data&#x27;], dtype=&#x27;&lt;U4&#x27;)</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'>2.718e+05 2.718e+05 ... 3.224e+05</div><input id='attrs-e9d9dcf8-66f8-4438-8a9c-83136cea2717' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e9d9dcf8-66f8-4438-8a9c-83136cea2717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce041a7e-3592-4ebd-8431-6c2e658a6b4c' class='xr-var-data-in' type='checkbox'><label for='data-ce041a7e-3592-4ebd-8431-6c2e658a6b4c' 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([271760., 271770., 271780., ..., 322360., 322370., 322380.])</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'>1.639e+06 1.639e+06 ... 1.6e+06</div><input id='attrs-6e11f17f-e245-4e76-86d3-3441c663f0be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e11f17f-e245-4e76-86d3-3441c663f0be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b20b288-5350-4ca8-a8b5-98f1a22e7819' class='xr-var-data-in' type='checkbox'><label for='data-5b20b288-5350-4ca8-a8b5-98f1a22e7819' 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([1639210., 1639200., 1639190., ..., 1600000., 1599990., 1599980.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>label:classes</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;name&#x27;: &#x27;&#x27;, &#x27;classes&#x27;: [&#x27;nodata...</div><input id='attrs-e21c75af-3b1b-4e68-8a17-899114c641a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e21c75af-3b1b-4e68-8a17-899114c641a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-289dab7d-6af4-44ff-abc4-e8199261f35b' class='xr-var-data-in' type='checkbox'><label for='data-289dab7d-6af4-44ff-abc4-e8199261f35b' 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({&#x27;name&#x27;: &#x27;&#x27;, &#x27;classes&#x27;: [&#x27;nodata&#x27;, &#x27;water&#x27;, &#x27;trees&#x27;, &#x27;grass&#x27;, &#x27;flooded veg&#x27;, &#x27;crops&#x27;, &#x27;scrub&#x27;, &#x27;built area&#x27;, &#x27;bare&#x27;, &#x27;snow/ice&#x27;, &#x27;clouds&#x27;]},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>end_datetime</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;2021-01-01T00:00:00Z&#x27;</div><input id='attrs-2f410ffd-6c8a-45ce-bfad-13199f2a1fac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f410ffd-6c8a-45ce-bfad-13199f2a1fac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d6e7c5a-0a96-4edb-b20e-c312aa465b50' class='xr-var-data-in' type='checkbox'><label for='data-6d6e7c5a-0a96-4edb-b20e-c312aa465b50' 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(&#x27;2021-01-01T00:00:00Z&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:bbox</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{908347.1216733564, 137987.12167...</div><input id='attrs-176f8811-2577-4c67-a005-83d46191e3e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-176f8811-2577-4c67-a005-83d46191e3e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ea9035e-a4bd-49d0-a5db-35a045863238' class='xr-var-data-in' type='checkbox'><label for='data-4ea9035e-a4bd-49d0-a5db-35a045863238' 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({908347.1216733564, 137987.1216733564, 790452.9972735613, 1799862.9972735613},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:shape</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{77036, 100941}</div><input id='attrs-f13f5011-e76a-456d-842d-ad1edfb28223' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f13f5011-e76a-456d-842d-ad1edfb28223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2010ee23-bb6d-403d-806c-17e27adf6204' class='xr-var-data-in' type='checkbox'><label for='data-2010ee23-bb6d-403d-806c-17e27adf6204' 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({77036, 100941}, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>start_datetime</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;2020-01-01T00:00:00Z&#x27;</div><input id='attrs-6ebe22ab-5c6f-4924-855e-7f2bce04174f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ebe22ab-5c6f-4924-855e-7f2bce04174f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6255e50c-d472-4c8f-a3a8-cc3e154274aa' class='xr-var-data-in' type='checkbox'><label for='data-6255e50c-d472-4c8f-a3a8-cc3e154274aa' 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(&#x27;2020-01-01T00:00:00Z&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>label:description</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;lulc&#x27;</div><input id='attrs-8977ed06-2904-4924-88ee-3ce234267406' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8977ed06-2904-4924-88ee-3ce234267406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2c22c4f-81ab-4439-ba6a-1ab243cbe7bb' class='xr-var-data-in' type='checkbox'><label for='data-e2c22c4f-81ab-4439-ba6a-1ab243cbe7bb' 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(&#x27;lulc&#x27;, dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32651</div><input id='attrs-e00ed50e-6ef7-4510-bacc-50fb38a9c747' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e00ed50e-6ef7-4510-bacc-50fb38a9c747' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-413404df-840a-4cfd-87d5-7c1df57184c4' class='xr-var-data-in' type='checkbox'><label for='data-413404df-840a-4cfd-87d5-7c1df57184c4' 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(32651)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:transform</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{0.0, 137987.1216733564, 10.0, 1...</div><input id='attrs-07603cb3-e83f-4483-a2f4-0d2fac273029' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07603cb3-e83f-4483-a2f4-0d2fac273029' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c50b9183-6556-4fe1-b998-926f2d63ecd5' class='xr-var-data-in' type='checkbox'><label for='data-c50b9183-6556-4fe1-b998-926f2d63ecd5' 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({0.0, 137987.1216733564, 10.0, 1799862.9972735613, -10.0},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>label:type</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;raster&#x27;</div><input id='attrs-98486479-712f-4b03-810a-23d0124c0a12' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98486479-712f-4b03-810a-23d0124c0a12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f69a6d3-a4d1-4023-b110-c04beeb0915f' class='xr-var-data-in' type='checkbox'><label for='data-0f69a6d3-a4d1-4023-b110-c04beeb0915f' 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(&#x27;raster&#x27;, dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>io:supercell_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;51P&#x27;</div><input id='attrs-7720de59-8085-484a-a938-a75e060a36c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7720de59-8085-484a-a938-a75e060a36c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d60b518-250d-4024-87a0-65c1a55db163' class='xr-var-data-in' type='checkbox'><label for='data-9d60b518-250d-4024-87a0-65c1a55db163' 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(&#x27;51P&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raster:bands</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;nodata&#x27;: 0, &#x27;spatial_resolutio...</div><input id='attrs-8964fce4-473d-428a-b197-b6a169e561aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8964fce4-473d-428a-b197-b6a169e561aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb794530-3f12-4469-ac2f-2d8054c17985' class='xr-var-data-in' type='checkbox'><label for='data-bb794530-3f12-4469-ac2f-2d8054c17985' 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({&#x27;nodata&#x27;: 0, &#x27;spatial_resolution&#x27;: 10}, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32651</div><input id='attrs-2f49e3ac-f313-4e1b-ac22-1143584e7edc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f49e3ac-f313-4e1b-ac22-1143584e7edc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71b89847-8bd9-41a8-9554-f29c8d1d127f' class='xr-var-data-in' type='checkbox'><label for='data-71b89847-8bd9-41a8-9554-f29c8d1d127f' 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(32651)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-10371633-bf5e-4858-876b-a5a1cc38b63a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-10371633-bf5e-4858-876b-a5a1cc38b63a' 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>spec :</span></dt><dd>RasterSpec(epsg=32651, bounds=(271760.0, 1599970.0, 322390.0, 1639210.0), resolutions_xy=(10.0, 10.0))</dd><dt><span>crs :</span></dt><dd>epsg:32651</dd><dt><span>transform :</span></dt><dd>| 10.00, 0.00, 271760.00|\n",
       "| 0.00,-10.00, 1639210.00|\n",
       "| 0.00, 0.00, 1.00|</dd><dt><span>resolution :</span></dt><dd>10.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'stackstac-c32fed696ee8899b67549452eb38099a' (time: 1, band: 1, y: 3924, x: 5063)>\n",
       "dask.array<fetch_raster_window, shape=(1, 1, 3924, 5063), dtype=uint8, chunksize=(1, 1, 1024, 1024), chunktype=numpy.ndarray>\n",
       "Coordinates: (12/17)\n",
       "  * time               (time) datetime64[ns] 2020-06-01\n",
       "    id                 (time) <U8 '51P-2020'\n",
       "  * band               (band) <U4 'data'\n",
       "  * x                  (x) float64 2.718e+05 2.718e+05 ... 3.224e+05 3.224e+05\n",
       "  * y                  (y) float64 1.639e+06 1.639e+06 ... 1.6e+06 1.6e+06\n",
       "    label:classes      object {'name': '', 'classes': ['nodata', 'water', 'tr...\n",
       "    ...                 ...\n",
       "    proj:epsg          int64 32651\n",
       "    proj:transform     object {0.0, 137987.1216733564, 10.0, 1799862.99727356...\n",
       "    label:type         <U6 'raster'\n",
       "    io:supercell_id    <U3 '51P'\n",
       "    raster:bands       object {'nodata': 0, 'spatial_resolution': 10}\n",
       "    epsg               int64 32651\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32651, bounds=(271760.0, 1599970.0, 322390.0...\n",
       "    crs:         epsg:32651\n",
       "    transform:   | 10.00, 0.00, 271760.00|\\n| 0.00,-10.00, 1639210.00|\\n| 0.0...\n",
       "    resolution:  10.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The STAC metadata contains some information we'll want to use when creating\n",
    "# our merged dataset. Get the EPSG code of the first item and the nodata value.\n",
    "item = next(search.get_items())\n",
    "epsg = proj.ext(item).epsg\n",
    "nodata = raster.ext(item.assets[\"data\"]).bands[0].nodata\n",
    "items = [pc.sign(item).to_dict() for item in search.get_items()]\n",
    "bounds_latlon = rasterio.features.bounds(area_of_interest)\n",
    "\n",
    "# Create a single DataArray from out multiple resutls with the corresponding\n",
    "# rasters projected to a single CRS. Note that we set the dtype to ubyte, which\n",
    "# matches our data, since stackstac will use float64 by default.\n",
    "stack = stackstac.stack(\n",
    "    items, epsg=epsg, dtype=np.ubyte, fill_value=nodata, bounds_latlon=bounds_latlon\n",
    ")\n",
    "\n",
    "stack"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c8b22c9-9260-48af-8dc9-bb46fb531673",
   "metadata": {},
   "source": [
    "Start up a local Dask cluster to allow us to do parallel reads. Use the following URL to open a dashboard in the Hub's Dask Extension. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2161565e-163c-4996-a5cd-0c6b14390eee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/proxy/8787/status\n"
     ]
    }
   ],
   "source": [
    "client = dask_client(processes=False)\n",
    "print(f\"/proxy/{client.scheduler_info()['services']['dashboard']}/status\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0e8e4e2-c477-4a43-885e-59fc1f5a86fb",
   "metadata": {},
   "source": [
    "### Mosaic and clip the raster\n",
    "\n",
    "So far, we haven't read in any data. Stackstac has used the STAC metadata to construct a DataArray that will contain our Item data. Let's mosaic the rasters across the `time` dimension (remember, they're all from a single synthesized \"time\" from 2020) and drop the single `band` dimension. Finally, we ask Dask to read the actual data by calling `.compute()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5108587f-10d1-4b52-9861-3aeb161bce46",
   "metadata": {},
   "outputs": [
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       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\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: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",
       "  margin-bottom: 0;\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",
       "}\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-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",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;stackstac-c32fed696ee8899b67549452eb38099a&#x27; (y: 3924, x: 5063)&gt;\n",
       "array([[5, 5, 5, ..., 2, 2, 2],\n",
       "       [5, 5, 5, ..., 2, 2, 2],\n",
       "       [5, 5, 5, ..., 2, 2, 2],\n",
       "       ...,\n",
       "       [7, 7, 7, ..., 2, 2, 2],\n",
       "       [7, 7, 7, ..., 2, 2, 2],\n",
       "       [7, 7, 7, ..., 2, 2, 2]], dtype=uint8)\n",
       "Coordinates: (12/15)\n",
       "    band               &lt;U4 &#x27;data&#x27;\n",
       "  * x                  (x) float64 2.718e+05 2.718e+05 ... 3.224e+05 3.224e+05\n",
       "  * y                  (y) float64 1.639e+06 1.639e+06 ... 1.6e+06 1.6e+06\n",
       "    label:classes      object {&#x27;name&#x27;: &#x27;&#x27;, &#x27;classes&#x27;: [&#x27;nodata&#x27;, &#x27;water&#x27;, &#x27;tr...\n",
       "    end_datetime       &lt;U20 &#x27;2021-01-01T00:00:00Z&#x27;\n",
       "    proj:bbox          object {908347.1216733564, 137987.1216733564, 790452.9...\n",
       "    ...                 ...\n",
       "    proj:epsg          int64 32651\n",
       "    proj:transform     object {0.0, 137987.1216733564, 10.0, 1799862.99727356...\n",
       "    label:type         &lt;U6 &#x27;raster&#x27;\n",
       "    io:supercell_id    &lt;U3 &#x27;51P&#x27;\n",
       "    raster:bands       object {&#x27;nodata&#x27;: 0, &#x27;spatial_resolution&#x27;: 10}\n",
       "    epsg               int64 32651\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32651, bounds=(271760.0, 1599970.0, 322390.0...\n",
       "    crs:         epsg:32651\n",
       "    transform:   | 10.00, 0.00, 271760.00|\\n| 0.00,-10.00, 1639210.00|\\n| 0.0...\n",
       "    resolution:  10.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'stackstac-c32fed696ee8899b67549452eb38099a'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 3924</li><li><span class='xr-has-index'>x</span>: 5063</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ea7bc8c0-5098-455d-88d0-a4c2290ee1f4' class='xr-array-in' type='checkbox' checked><label for='section-ea7bc8c0-5098-455d-88d0-a4c2290ee1f4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>5 5 5 5 5 5 5 1 1 1 1 1 1 1 1 1 1 ... 2 2 2 2 2 2 2 2 6 6 6 6 6 2 2 2</span></div><div class='xr-array-data'><pre>array([[5, 5, 5, ..., 2, 2, 2],\n",
       "       [5, 5, 5, ..., 2, 2, 2],\n",
       "       [5, 5, 5, ..., 2, 2, 2],\n",
       "       ...,\n",
       "       [7, 7, 7, ..., 2, 2, 2],\n",
       "       [7, 7, 7, ..., 2, 2, 2],\n",
       "       [7, 7, 7, ..., 2, 2, 2]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-d5d5c386-edaa-44b1-8bc5-3f53ba6ca3e7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d5d5c386-edaa-44b1-8bc5-3f53ba6ca3e7' class='xr-section-summary' >Coordinates: <span>(15)</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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;data&#x27;</div><input id='attrs-cabbd8db-f69e-4925-a393-89bfa2196208' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cabbd8db-f69e-4925-a393-89bfa2196208' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2457b1fe-bfeb-4ae9-ab1d-0fda91a1fd0b' class='xr-var-data-in' type='checkbox'><label for='data-2457b1fe-bfeb-4ae9-ab1d-0fda91a1fd0b' 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(&#x27;data&#x27;, dtype=&#x27;&lt;U4&#x27;)</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'>2.718e+05 2.718e+05 ... 3.224e+05</div><input id='attrs-6179695b-59d7-4d3e-8c7d-897dab9f6c14' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6179695b-59d7-4d3e-8c7d-897dab9f6c14' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc660a05-0aef-4d2e-b57b-b8f52a4f1ae7' class='xr-var-data-in' type='checkbox'><label for='data-cc660a05-0aef-4d2e-b57b-b8f52a4f1ae7' 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([271760., 271770., 271780., ..., 322360., 322370., 322380.])</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'>1.639e+06 1.639e+06 ... 1.6e+06</div><input id='attrs-f27c6725-4db2-4977-bfc1-aaa23b7897e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f27c6725-4db2-4977-bfc1-aaa23b7897e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7d86eba-c9b8-4e7e-ad9f-213449ce581c' class='xr-var-data-in' type='checkbox'><label for='data-e7d86eba-c9b8-4e7e-ad9f-213449ce581c' 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([1639210., 1639200., 1639190., ..., 1600000., 1599990., 1599980.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>label:classes</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;name&#x27;: &#x27;&#x27;, &#x27;classes&#x27;: [&#x27;nodata...</div><input id='attrs-2f4b4db1-bd8a-4b21-bb7d-980c56d140c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f4b4db1-bd8a-4b21-bb7d-980c56d140c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f9357c5-b15d-4a7b-b104-b129215d62d7' class='xr-var-data-in' type='checkbox'><label for='data-1f9357c5-b15d-4a7b-b104-b129215d62d7' 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({&#x27;name&#x27;: &#x27;&#x27;, &#x27;classes&#x27;: [&#x27;nodata&#x27;, &#x27;water&#x27;, &#x27;trees&#x27;, &#x27;grass&#x27;, &#x27;flooded veg&#x27;, &#x27;crops&#x27;, &#x27;scrub&#x27;, &#x27;built area&#x27;, &#x27;bare&#x27;, &#x27;snow/ice&#x27;, &#x27;clouds&#x27;]},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>end_datetime</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;2021-01-01T00:00:00Z&#x27;</div><input id='attrs-cdd5d0af-c61e-45ed-b0a7-a523cab2d1e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cdd5d0af-c61e-45ed-b0a7-a523cab2d1e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5f80a00-72ad-46ad-a6bc-28b95f065893' class='xr-var-data-in' type='checkbox'><label for='data-f5f80a00-72ad-46ad-a6bc-28b95f065893' 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(&#x27;2021-01-01T00:00:00Z&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:bbox</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{908347.1216733564, 137987.12167...</div><input id='attrs-73945fcb-4fa3-4c13-9996-761c484a0a74' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73945fcb-4fa3-4c13-9996-761c484a0a74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-153e166c-3729-47ce-b098-1a5bda7e3973' class='xr-var-data-in' type='checkbox'><label for='data-153e166c-3729-47ce-b098-1a5bda7e3973' 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({908347.1216733564, 137987.1216733564, 790452.9972735613, 1799862.9972735613},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:shape</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{77036, 100941}</div><input id='attrs-0fbd9a57-01fc-4474-a134-bd90d8714ea0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0fbd9a57-01fc-4474-a134-bd90d8714ea0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a31f68e-d2da-4603-af86-0025d6bfadd7' class='xr-var-data-in' type='checkbox'><label for='data-3a31f68e-d2da-4603-af86-0025d6bfadd7' 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({77036, 100941}, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>start_datetime</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;2020-01-01T00:00:00Z&#x27;</div><input id='attrs-f3326c09-1712-428a-b43f-cb1732471304' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3326c09-1712-428a-b43f-cb1732471304' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44caaa19-01fc-4daf-9aac-d8f611f0afe2' class='xr-var-data-in' type='checkbox'><label for='data-44caaa19-01fc-4daf-9aac-d8f611f0afe2' 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(&#x27;2020-01-01T00:00:00Z&#x27;, dtype=&#x27;&lt;U20&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>label:description</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;lulc&#x27;</div><input id='attrs-2ebc5c56-7756-41d3-8161-07505e015098' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ebc5c56-7756-41d3-8161-07505e015098' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-478e1566-2623-4344-bc8f-e099945ab9cf' class='xr-var-data-in' type='checkbox'><label for='data-478e1566-2623-4344-bc8f-e099945ab9cf' 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(&#x27;lulc&#x27;, dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32651</div><input id='attrs-4be8163d-1df9-44e9-8946-b892717c0a37' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4be8163d-1df9-44e9-8946-b892717c0a37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-684433dc-ae1f-46ec-bcae-86e0d9bd2ba3' class='xr-var-data-in' type='checkbox'><label for='data-684433dc-ae1f-46ec-bcae-86e0d9bd2ba3' 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(32651)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:transform</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{0.0, 137987.1216733564, 10.0, 1...</div><input id='attrs-9b7854d8-e27e-4aa5-9407-a6d14a789fc5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b7854d8-e27e-4aa5-9407-a6d14a789fc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6281f8ab-85e9-4ce0-aad4-b9d92f5a396d' class='xr-var-data-in' type='checkbox'><label for='data-6281f8ab-85e9-4ce0-aad4-b9d92f5a396d' 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({0.0, 137987.1216733564, 10.0, 1799862.9972735613, -10.0},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>label:type</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;raster&#x27;</div><input id='attrs-a6e7c421-52c3-4419-803e-b9bb52ee2de2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6e7c421-52c3-4419-803e-b9bb52ee2de2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0664dd41-54f6-4b44-b46f-18b9aa7d5294' class='xr-var-data-in' type='checkbox'><label for='data-0664dd41-54f6-4b44-b46f-18b9aa7d5294' 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(&#x27;raster&#x27;, dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>io:supercell_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;51P&#x27;</div><input id='attrs-049708d8-da6c-473a-91ec-a18ef11b3d1c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-049708d8-da6c-473a-91ec-a18ef11b3d1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eef5df24-11d2-4074-ae65-d820afe827a0' class='xr-var-data-in' type='checkbox'><label for='data-eef5df24-11d2-4074-ae65-d820afe827a0' 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(&#x27;51P&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raster:bands</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;nodata&#x27;: 0, &#x27;spatial_resolutio...</div><input id='attrs-22641c75-d273-486b-b2b1-293853e705da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22641c75-d273-486b-b2b1-293853e705da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e7ce2cf-63c4-4c6e-8ec7-acdee53bca00' class='xr-var-data-in' type='checkbox'><label for='data-6e7ce2cf-63c4-4c6e-8ec7-acdee53bca00' 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({&#x27;nodata&#x27;: 0, &#x27;spatial_resolution&#x27;: 10}, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32651</div><input id='attrs-c7bc25e7-c43d-43e6-a8a0-f465f68b0dda' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c7bc25e7-c43d-43e6-a8a0-f465f68b0dda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5042820-e2f6-4503-84b6-2c2cbcb418e1' class='xr-var-data-in' type='checkbox'><label for='data-b5042820-e2f6-4503-84b6-2c2cbcb418e1' 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(32651)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b0755f0f-7d3c-4dff-8cc2-0f284a345739' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b0755f0f-7d3c-4dff-8cc2-0f284a345739' 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>spec :</span></dt><dd>RasterSpec(epsg=32651, bounds=(271760.0, 1599970.0, 322390.0, 1639210.0), resolutions_xy=(10.0, 10.0))</dd><dt><span>crs :</span></dt><dd>epsg:32651</dd><dt><span>transform :</span></dt><dd>| 10.00, 0.00, 271760.00|\n",
       "| 0.00,-10.00, 1639210.00|\n",
       "| 0.00, 0.00, 1.00|</dd><dt><span>resolution :</span></dt><dd>10.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'stackstac-c32fed696ee8899b67549452eb38099a' (y: 3924, x: 5063)>\n",
       "array([[5, 5, 5, ..., 2, 2, 2],\n",
       "       [5, 5, 5, ..., 2, 2, 2],\n",
       "       [5, 5, 5, ..., 2, 2, 2],\n",
       "       ...,\n",
       "       [7, 7, 7, ..., 2, 2, 2],\n",
       "       [7, 7, 7, ..., 2, 2, 2],\n",
       "       [7, 7, 7, ..., 2, 2, 2]], dtype=uint8)\n",
       "Coordinates: (12/15)\n",
       "    band               <U4 'data'\n",
       "  * x                  (x) float64 2.718e+05 2.718e+05 ... 3.224e+05 3.224e+05\n",
       "  * y                  (y) float64 1.639e+06 1.639e+06 ... 1.6e+06 1.6e+06\n",
       "    label:classes      object {'name': '', 'classes': ['nodata', 'water', 'tr...\n",
       "    end_datetime       <U20 '2021-01-01T00:00:00Z'\n",
       "    proj:bbox          object {908347.1216733564, 137987.1216733564, 790452.9...\n",
       "    ...                 ...\n",
       "    proj:epsg          int64 32651\n",
       "    proj:transform     object {0.0, 137987.1216733564, 10.0, 1799862.99727356...\n",
       "    label:type         <U6 'raster'\n",
       "    io:supercell_id    <U3 '51P'\n",
       "    raster:bands       object {'nodata': 0, 'spatial_resolution': 10}\n",
       "    epsg               int64 32651\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32651, bounds=(271760.0, 1599970.0, 322390.0...\n",
       "    crs:         epsg:32651\n",
       "    transform:   | 10.00, 0.00, 271760.00|\\n| 0.00,-10.00, 1639210.00|\\n| 0.0...\n",
       "    resolution:  10.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nodata = {\"nodata\": 0} if stackstac.__version__ >= \"0.3.0\" else {}\n",
    "merged = stackstac.mosaic(stack, dim=\"time\", axis=None, **nodata).squeeze().compute()\n",
    "merged"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5f31c78-fe4d-4b0d-bdcb-0289abc7e860",
   "metadata": {},
   "source": [
    "Now a quick plot to check that we've got the data we want."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "534e9b80-3c86-4029-a236-14653df64333",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc3c5100-12f2-4488-a19a-cc174efeee6e",
   "metadata": {},
   "source": [
    "It looks good, but it doesn't look like a land cover map. The source GeoTIFFs contain a colormap and the STAC metadata contains the class names. We'll open one of the source files just to read this metadata and construct the right colors and names for our plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "17570d98-c60a-4aa9-a6fa-9164cb9ba733",
   "metadata": {},
   "outputs": [],
   "source": [
    "class_names = merged.coords[\"label:classes\"].item()[\"classes\"]\n",
    "class_count = len(class_names)\n",
    "\n",
    "with rasterio.open(pc.sign(item.assets[\"data\"].href)) as src:\n",
    "    colormap_def = src.colormap(1)  # get metadata colormap for band 1\n",
    "    colormap = [\n",
    "        np.array(colormap_def[i]) / 255 for i in range(class_count)\n",
    "    ]  # transform to matplotlib color format\n",
    "\n",
    "cmap = ListedColormap(colormap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b9d365ca-a063-4640-a00f-731f340f40d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(12, 6), dpi=125, subplot_kw=dict(projection=ccrs.epsg(epsg)), frameon=False\n",
    ")\n",
    "p = merged.plot(\n",
    "    ax=ax,\n",
    "    transform=ccrs.epsg(epsg),\n",
    "    cmap=cmap,\n",
    "    add_colorbar=False,\n",
    "    vmin=0,\n",
    "    vmax=class_count,\n",
    ")\n",
    "ax.set_title(\"Manila 2020 LULC\")\n",
    "\n",
    "cbar = plt.colorbar(p)\n",
    "cbar.set_ticks(range(class_count))\n",
    "cbar.set_ticklabels(class_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e742d47e-dda6-4bdf-a441-854f23b3f752",
   "metadata": {},
   "source": [
    "That looks better. Let's also plot a histogram of the pixel values to see the distribution of land cover types within our area of interest. We can reuse the colormap we generated to help tie the two visualizations together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "746155c1-1a24-4696-b2f4-ae2deef5990e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = list(cmap.colors)\n",
    "\n",
    "ax = (\n",
    "    pd.value_counts(merged.data.ravel(), sort=False)\n",
    "    .sort_index()\n",
    "    .reindex(range(len(colors)), fill_value=0)\n",
    "    .rename(dict(enumerate(class_names)))\n",
    "    .plot.barh(color=colors, rot=0, width=0.9)\n",
    ")\n",
    "ax.set(\n",
    "    title=\"Distribution of Land Cover classes\",\n",
    "    ylabel=\"Landcover class\",\n",
    "    xlabel=\"Pixel count\",\n",
    ");"
   ]
  }
 ],
 "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": "3.9.9"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "1a8b2d5968154b7eb215b863ec2f3d67": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "d5688f16026940738b3af4cf6e523105": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "VBoxModel",
      "state": {
       "layout": "IPY_MODEL_1a8b2d5968154b7eb215b863ec2f3d67"
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}