notebooks/src/planetary-computer-reading-stac.ipynb

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    "## Reading Data from the STAC API\n",
    "\n",
    "The Planetary Computer catalogs the datasets we host using the [STAC](http://stacspec.org/) (SpatioTemporal Asset Catalog) specification. We provide a [STAC API](https://github.com/radiantearth/stac-api-spec) endpoint that can be used to search our datasets by space, time, and more. This quickstart will show you how to search for data using our STAC API and open-source Python libraries. For more on how to use our STAC API from R, see [Reading data from the STAC API with R](https://planetarycomputer.microsoft.com/docs/quickstarts/reading-stac-r/).\n",
    "\n",
    "To get started you'll need the [pystac-client](https://github.com/stac-utils/pystac-client) library installed. You can install it via pip:\n",
    "\n",
    "```\n",
    "> pip install pystac-client\n",
    "```\n",
    "\n",
    "First we'll use pystac-client to open up our STAC API:"
    ]
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    "source": [
    "from pystac_client import Client\n",
    "\n",
    "catalog = Client.open(\"https://planetarycomputer.microsoft.com/api/stac/v1\")"
    ]
    },
    {
    "cell_type": "markdown",
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    "### Searching\n",
    "\n",
    "We can use the STAC API to search for assets meeting some criteria. This might include the date and time the asset covers, is spatial extent, or any other property captured in the STAC item's metadata.\n",
    "\n",
    "In this example we'll search for imagery from [Landsat Collection 2 Level-2](https://planetarycomputer.microsoft.com/dataset/landsat-c2-l2) area around Microsoft's main campus in December of 2020."
    ]
    },
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    "4"
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    "source": [
    "time_range = \"2020-12-01/2020-12-31\"\n",
    "bbox = [-122.2751, 47.5469, -121.9613, 47.7458]\n",
    "\n",
    "search = catalog.search(collections=[\"landsat-8-c2-l2\"], bbox=bbox, datetime=time_range)\n",
    "items = search.get_all_items()\n",
    "len(items)"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "84143827-ff63-4946-a995-ebc101f18d52",
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    "source": [
    "In that example our spatial query used a bounding box with a `bbox`. Alternatively, you can pass a GeoJSON object as `intersects`\n",
    "\n",
    "```python\n",
    "area_of_interest = {\n",
    "    \"type\": \"Polygon\",\n",
    "    \"coordinates\": [\n",
    "        [\n",
    "            [-122.2751, 47.5469],\n",
    "            [-121.9613, 47.9613],\n",
    "            [-121.9613, 47.9613],\n",
    "            [-122.2751, 47.9613],\n",
    "            [-122.2751, 47.5469],\n",
    "        ]\n",
    "    ],\n",
    "}\n",
    "\n",
    "time_range = \"2020-12-01/2020-12-31\"\n",
    "\n",
    "search = catalog.search(\n",
    "    collections=[\"landsat-8-c2-l2\"], intersects=area_of_interest, datetime=time_range\n",
    ")\n",
    "```"
    ]
    },
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    "id": "aedaf9f7-1ba2-472d-85e1-5838e7df9ffb",
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    "source": [
    "`items` is a [`pystac.ItemCollection`](https://pystac.readthedocs.io/en/stable/api/item_collection.html#pystac-item-collection). We can see that 4 items matched our search criteria."
    ]
    },
    {
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    "4"
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    "execution_count": 3,
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    ],
    "source": [
    "len(items)"
    ]
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    "source": [
    "Each [`pystac.Item`](https://pystac.readthedocs.io/en/stable/api/pystac.html#pystac.Item) in this `ItemCollection` includes all the metadata for that scene. [STAC Items](https://github.com/radiantearth/stac-spec/blob/master/item-spec/item-spec.md) are GeoJSON features, and so can be loaded by libraries like [geopandas](http://geopandas.readthedocs.io/)."
    ]
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    "  <thead>\n",
    "    <tr style=\"text-align: right;\">\n",
    "      <th></th>\n",
    "      <th>geometry</th>\n",
    "      <th>datetime</th>\n",
    "      <th>platform</th>\n",
    "      <th>proj:bbox</th>\n",
    "      <th>proj:epsg</th>\n",
    "      <th>description</th>\n",
    "      <th>instruments</th>\n",
    "      <th>eo:cloud_cover</th>\n",
    "      <th>view:off_nadir</th>\n",
    "      <th>landsat:wrs_row</th>\n",
    "      <th>landsat:scene_id</th>\n",
    "      <th>landsat:wrs_path</th>\n",
    "      <th>landsat:wrs_type</th>\n",
    "      <th>view:sun_azimuth</th>\n",
    "      <th>view:sun_elevation</th>\n",
    "      <th>landsat:cloud_cover_land</th>\n",
    "      <th>landsat:processing_level</th>\n",
    "      <th>landsat:collection_number</th>\n",
    "      <th>landsat:collection_category</th>\n",
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    "  </thead>\n",
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    "      <th>0</th>\n",
    "      <td>POLYGON ((-122.74802 48.51223, -120.22983 48.0...</td>\n",
    "      <td>2020-12-29T18:55:56.738265Z</td>\n",
    "      <td>landsat-8</td>\n",
    "      <td>[471585.0, 5136885.0, 705015.0, 5373315.0]</td>\n",
    "      <td>32610</td>\n",
    "      <td>Landsat Collection 2 Level-2 Surface Reflectan...</td>\n",
    "      <td>[oli, tirs]</td>\n",
    "      <td>100.00</td>\n",
    "      <td>0</td>\n",
    "      <td>027</td>\n",
    "      <td>LC80460272020364LGN00</td>\n",
    "      <td>046</td>\n",
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    "      <td>162.253231</td>\n",
    "      <td>17.458298</td>\n",
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    "      <td>landsat-8</td>\n",
    "      <td>[353385.0, 5135085.0, 589215.0, 5374215.0]</td>\n",
    "      <td>32610</td>\n",
    "      <td>Landsat Collection 2 Level-2 Surface Reflectan...</td>\n",
    "      <td>[oli, tirs]</td>\n",
    "      <td>100.00</td>\n",
    "      <td>0</td>\n",
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    "      <td>LC80470272020355LGN00</td>\n",
    "      <td>047</td>\n",
    "      <td>2</td>\n",
    "      <td>163.360118</td>\n",
    "      <td>17.414441</td>\n",
    "      <td>100.00</td>\n",
    "      <td>L2SP</td>\n",
    "      <td>02</td>\n",
    "      <td>T2</td>\n",
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    "    <tr>\n",
    "      <th>2</th>\n",
    "      <td>POLYGON ((-122.75189 48.51190, -120.23406 48.0...</td>\n",
    "      <td>2020-12-13T18:56:00.096447Z</td>\n",
    "      <td>landsat-8</td>\n",
    "      <td>[471285.0, 5136885.0, 704715.0, 5373315.0]</td>\n",
    "      <td>32610</td>\n",
    "      <td>Landsat Collection 2 Level-2 Surface Reflectan...</td>\n",
    "      <td>[oli, tirs]</td>\n",
    "      <td>98.73</td>\n",
    "      <td>0</td>\n",
    "      <td>027</td>\n",
    "      <td>LC80460272020348LGN00</td>\n",
    "      <td>046</td>\n",
    "      <td>2</td>\n",
    "      <td>164.126188</td>\n",
    "      <td>17.799744</td>\n",
    "      <td>98.64</td>\n",
    "      <td>L2SP</td>\n",
    "      <td>02</td>\n",
    "      <td>T2</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>3</th>\n",
    "      <td>POLYGON ((-124.29534 48.51347, -121.78981 48.0...</td>\n",
    "      <td>2020-12-04T19:02:11.194486Z</td>\n",
    "      <td>landsat-8</td>\n",
    "      <td>[353685.0, 5135085.0, 589515.0, 5374215.0]</td>\n",
    "      <td>32610</td>\n",
    "      <td>Landsat Collection 2 Level-2 Surface Reflectan...</td>\n",
    "      <td>[oli, tirs]</td>\n",
    "      <td>1.55</td>\n",
    "      <td>0</td>\n",
    "      <td>027</td>\n",
    "      <td>LC80470272020339LGN00</td>\n",
    "      <td>047</td>\n",
    "      <td>2</td>\n",
    "      <td>164.914060</td>\n",
    "      <td>18.807230</td>\n",
    "      <td>1.90</td>\n",
    "      <td>L2SP</td>\n",
    "      <td>02</td>\n",
    "      <td>T1</td>\n",
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    "                                            geometry  \\\n",
    "0  POLYGON ((-122.74802 48.51223, -120.22983 48.0...   \n",
    "1  POLYGON ((-124.29833 48.51325, -121.79248 48.0...   \n",
    "2  POLYGON ((-122.75189 48.51190, -120.23406 48.0...   \n",
    "3  POLYGON ((-124.29534 48.51347, -121.78981 48.0...   \n",
    "\n",
    "                      datetime   platform  \\\n",
    "0  2020-12-29T18:55:56.738265Z  landsat-8   \n",
    "1  2020-12-20T19:02:09.878796Z  landsat-8   \n",
    "2  2020-12-13T18:56:00.096447Z  landsat-8   \n",
    "3  2020-12-04T19:02:11.194486Z  landsat-8   \n",
    "\n",
    "                                    proj:bbox  proj:epsg  \\\n",
    "0  [471585.0, 5136885.0, 705015.0, 5373315.0]      32610   \n",
    "1  [353385.0, 5135085.0, 589215.0, 5374215.0]      32610   \n",
    "2  [471285.0, 5136885.0, 704715.0, 5373315.0]      32610   \n",
    "3  [353685.0, 5135085.0, 589515.0, 5374215.0]      32610   \n",
    "\n",
    "                                         description  instruments  \\\n",
    "0  Landsat Collection 2 Level-2 Surface Reflectan...  [oli, tirs]   \n",
    "1  Landsat Collection 2 Level-2 Surface Reflectan...  [oli, tirs]   \n",
    "2  Landsat Collection 2 Level-2 Surface Reflectan...  [oli, tirs]   \n",
    "3  Landsat Collection 2 Level-2 Surface Reflectan...  [oli, tirs]   \n",
    "\n",
    "   eo:cloud_cover  view:off_nadir landsat:wrs_row       landsat:scene_id  \\\n",
    "0          100.00               0             027  LC80460272020364LGN00   \n",
    "1          100.00               0             027  LC80470272020355LGN00   \n",
    "2           98.73               0             027  LC80460272020348LGN00   \n",
    "3            1.55               0             027  LC80470272020339LGN00   \n",
    "\n",
    "  landsat:wrs_path landsat:wrs_type  view:sun_azimuth  view:sun_elevation  \\\n",
    "0              046                2        162.253231           17.458298   \n",
    "1              047                2        163.360118           17.414441   \n",
    "2              046                2        164.126188           17.799744   \n",
    "3              047                2        164.914060           18.807230   \n",
    "\n",
    "   landsat:cloud_cover_land landsat:processing_level  \\\n",
    "0                    100.00                     L2SP   \n",
    "1                    100.00                     L2SP   \n",
    "2                     98.64                     L2SP   \n",
    "3                      1.90                     L2SP   \n",
    "\n",
    "  landsat:collection_number landsat:collection_category  \n",
    "0                        02                          T2  \n",
    "1                        02                          T2  \n",
    "2                        02                          T2  \n",
    "3                        02                          T1  "
    ]
    },
    "execution_count": 4,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "import geopandas\n",
    "\n",
    "df = geopandas.GeoDataFrame.from_features(items.to_dict(), crs=\"epsg:4326\")\n",
    "df"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "e88bc7eb-fd2f-48b1-a3d7-dc96d8b7635c",
    "metadata": {},
    "source": [
    "We can use the `eo` extension to sort the items by cloudiness. We'll grab an item with low cloudiness:"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 5,
    "id": "c60accc9-4126-4609-8a65-406719b5485b",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/plain": [
    "<Item id=LC08_L2SP_047027_20201204_02_T1>"
    ]
    },
    "execution_count": 5,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "selected_item = min(items, key=lambda item: item.properties[\"eo:cloud_cover\"])\n",
    "selected_item"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "9be696c5-c9b9-4dcb-a876-a645d384fa83",
    "metadata": {},
    "source": [
    "Each STAC item has one or more [Assets](https://github.com/radiantearth/stac-spec/blob/master/item-spec/item-spec.md#asset-object), which include links to the actual files."
    ]
    },
    {
    "cell_type": "code",
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    "id": "f507b45d-5985-4f10-9850-c1b3947c9908",
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    "text/html": [
    "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
    "┃<span style=\"font-weight: bold\"> Asset Key                 </span>┃<span style=\"font-weight: bold\"> Descripiption                                  </span>┃\n",
    "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
    "│ ANG                       │ Angle Coefficients File                        │\n",
    "│ SR_B1                     │ Coastal/Aerosol Band (B1)                      │\n",
    "│ SR_B2                     │ Blue Band (B2)                                 │\n",
    "│ SR_B3                     │ Green Band (B3)                                │\n",
    "│ SR_B4                     │ Red Band (B4)                                  │\n",
    "│ SR_B5                     │ Near Infrared Band 0.8 (B5)                    │\n",
    "│ SR_B6                     │ Short-wave Infrared Band 1.6 (B6)              │\n",
    "│ SR_B7                     │ Short-wave Infrared Band 2.2 (B7)              │\n",
    "│ ST_QA                     │ Surface Temperature Quality Assessment Band    │\n",
    "│ ST_B10                    │ Surface Temperature Band (B10)                 │\n",
    "│ MTL.txt                   │ Product Metadata File                          │\n",
    "│ MTL.xml                   │ Product Metadata File (xml)                    │\n",
    "│ ST_DRAD                   │ Downwelled Radiance Band                       │\n",
    "│ ST_EMIS                   │ Emissivity Band                                │\n",
    "│ ST_EMSD                   │ Emissivity Standard Deviation Band             │\n",
    "│ ST_TRAD                   │ Thermal Radiance Band                          │\n",
    "│ ST_URAD                   │ Upwelled Radiance Band                         │\n",
    "│ MTL.json                  │ Product Metadata File (json)                   │\n",
    "│ QA_PIXEL                  │ Pixel Quality Assessment Band                  │\n",
    "│ ST_ATRAN                  │ Atmospheric Transmittance Band                 │\n",
    "│ ST_CDIST                  │ Cloud Distance Band                            │\n",
    "│ QA_RADSAT                 │ Radiometric Saturation Quality Assessment Band │\n",
    "│ thumbnail                 │ Thumbnail image                                │\n",
    "│ SR_QA_AEROSOL             │ Aerosol Quality Analysis Band                  │\n",
    "│ reduced_resolution_browse │ Reduced resolution browse image                │\n",
    "│ tilejson                  │ TileJSON with default rendering                │\n",
    "│ rendered_preview          │ Rendered preview                               │\n",
    "└───────────────────────────┴────────────────────────────────────────────────┘\n",
    "</pre>\n"
    ],
    "text/plain": [
    "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
    "┃\u001b[1m \u001b[0m\u001b[1mAsset Key                \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mDescripiption                                 \u001b[0m\u001b[1m \u001b[0m┃\n",
    "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
    "│ ANG                       │ Angle Coefficients File                        │\n",
    "│ SR_B1                     │ Coastal/Aerosol Band (B1)                      │\n",
    "│ SR_B2                     │ Blue Band (B2)                                 │\n",
    "│ SR_B3                     │ Green Band (B3)                                │\n",
    "│ SR_B4                     │ Red Band (B4)                                  │\n",
    "│ SR_B5                     │ Near Infrared Band 0.8 (B5)                    │\n",
    "│ SR_B6                     │ Short-wave Infrared Band 1.6 (B6)              │\n",
    "│ SR_B7                     │ Short-wave Infrared Band 2.2 (B7)              │\n",
    "│ ST_QA                     │ Surface Temperature Quality Assessment Band    │\n",
    "│ ST_B10                    │ Surface Temperature Band (B10)                 │\n",
    "│ MTL.txt                   │ Product Metadata File                          │\n",
    "│ MTL.xml                   │ Product Metadata File (xml)                    │\n",
    "│ ST_DRAD                   │ Downwelled Radiance Band                       │\n",
    "│ ST_EMIS                   │ Emissivity Band                                │\n",
    "│ ST_EMSD                   │ Emissivity Standard Deviation Band             │\n",
    "│ ST_TRAD                   │ Thermal Radiance Band                          │\n",
    "│ ST_URAD                   │ Upwelled Radiance Band                         │\n",
    "│ MTL.json                  │ Product Metadata File (json)                   │\n",
    "│ QA_PIXEL                  │ Pixel Quality Assessment Band                  │\n",
    "│ ST_ATRAN                  │ Atmospheric Transmittance Band                 │\n",
    "│ ST_CDIST                  │ Cloud Distance Band                            │\n",
    "│ QA_RADSAT                 │ Radiometric Saturation Quality Assessment Band │\n",
    "│ thumbnail                 │ Thumbnail image                                │\n",
    "│ SR_QA_AEROSOL             │ Aerosol Quality Analysis Band                  │\n",
    "│ reduced_resolution_browse │ Reduced resolution browse image                │\n",
    "│ tilejson                  │ TileJSON with default rendering                │\n",
    "│ rendered_preview          │ Rendered preview                               │\n",
    "└───────────────────────────┴────────────────────────────────────────────────┘\n"
    ]
    },
    "execution_count": 6,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "import rich.table\n",
    "\n",
    "table = rich.table.Table(\"Asset Key\", \"Descripiption\")\n",
    "for asset_key, asset in selected_item.assets.items():\n",
    "    # print(f\"{asset_key:<25} - {asset.title}\")\n",
    "    table.add_row(asset_key, asset.title)\n",
    "\n",
    "table"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "fe4053e4-6c1e-46b7-947d-79811a2877e4",
    "metadata": {},
    "source": [
    "Here, we'll inspect the `rendered_preview` asset."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 7,
    "id": "f175aa10-8f97-4ea3-8fda-c6fe4469baea",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/plain": [
    "{'href': 'https://planetarycomputer.microsoft.com/api/data/v1/item/preview.png?collection=landsat-8-c2-l2&item=LC08_L2SP_047027_20201204_02_T1&assets=SR_B4&assets=SR_B3&assets=SR_B2&color_formula=gamma+RGB+2.7%2C+saturation+1.5%2C+sigmoidal+RGB+15+0.55',\n",
    " 'type': 'image/png',\n",
    " 'title': 'Rendered preview',\n",
    " 'rel': 'preview',\n",
    " 'roles': ['overview']}"
    ]
    },
    "execution_count": 7,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "selected_item.assets[\"rendered_preview\"].to_dict()"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 8,
    "id": "50535606-4891-40d4-9e52-7d0056583681",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/html": [
    "<img src=\"https://planetarycomputer.microsoft.com/api/data/v1/item/preview.png?collection=landsat-8-c2-l2&item=LC08_L2SP_047027_20201204_02_T1&assets=SR_B4&assets=SR_B3&assets=SR_B2&color_formula=gamma+RGB+2.7%2C+saturation+1.5%2C+sigmoidal+RGB+15+0.55\" width=\"500\"/>"
    ],
    "text/plain": [
    "<IPython.core.display.Image object>"
    ]
    },
    "execution_count": 8,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "from IPython.display import Image\n",
    "\n",
    "Image(url=selected_item.assets[\"rendered_preview\"].href, width=500)"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "5abf7884-00c5-49fd-b27f-a57a23c00af5",
    "metadata": {},
    "source": [
    "That `rendered_preview` asset is generated dynamically from the raw data using the Planetary Computer's [data API](http://planetarycomputer.microsoft.com/api/data/v1/). We can access the raw data, stored as Cloud Optimzied GeoTIFFs in Azure Blob Storage, using one of the other assets. That said, we do need to do one more thing before accessing the data. If we simply made a request to the file in blob storage we'd get a 404:"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 9,
    "id": "aefcb71d-31ba-4211-b7a5-7966c13304ef",
    "metadata": {},
    "outputs": [
    {
    "name": "stdout",
    "output_type": "stream",
    "text": [
    "Accessing https://landsateuwest.blob.core.windows.net/landsat-c2/level-2/standard/oli-tirs/2020/047/027/LC08_L2SP_047027_20201204_20210313_02_T1/LC08_L2SP_047027_20201204_20210313_02_T1_SR_B2.TIF\n"
    ]
    },
    {
    "data": {
    "text/plain": [
    "<Response [404]>"
    ]
    },
    "execution_count": 9,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "import requests\n",
    "\n",
    "url = selected_item.assets[\"SR_B2\"].href\n",
    "print(\"Accessing\", url)\n",
    "response = requests.get(url)\n",
    "response"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "65686af5-414e-4482-af27-fb680b179930",
    "metadata": {},
    "source": [
    "That's because the Plantary Computer uses Azure Blob Storage [SAS Tokens](https://docs.microsoft.com/en-us/azure/storage/common/storage-sas-overview#how-a-shared-access-signature-works) to enable access to our data, which allows us to provide the data for free to anyone, anywhere while maintaining some control over the amount of egress for datasets.\n",
    "\n",
    "To get a token for access, you can use the Planetary Computer's [Data Authentication API](../reference/sas.md). You can access that anonymously, or you can provide an API Key for higher rate limits and longer-lived tokens.\n",
    "\n",
    "You can also use the [planetary-computer](https://github.com/microsoft/planetary-computer-sdk-for-python) package to generate tokens and sign asset HREFs for access. You can install via pip with\n",
    "\n",
    "```\n",
    "> pip install planetary-computer\n",
    "```"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 10,
    "id": "08f7fdcb-8d15-45a7-be8d-2e4d45cf96b1",
    "metadata": {},
    "outputs": [],
    "source": [
    "import planetary_computer\n",
    "\n",
    "# PC_SDK_SUBSCRIPTION_KEY\n",
    "signed_href = planetary_computer.sign(selected_item).assets[\"SR_B2\"].href"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "29feea6d-400d-4573-82ba-835918adb701",
    "metadata": {},
    "source": [
    "We can load up that single COG using libraries like [rioxarray](https://corteva.github.io/rioxarray/html/rioxarray.html) or [rasterio](https://rasterio.readthedocs.io/en/latest/)"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 11,
    "id": "58481f78-40b5-486d-bf36-ab333206bdb4",
    "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": [
    "# import xarray as xr\n",
    "import rioxarray\n",
    "\n",
    "ds = rioxarray.open_rasterio(signed_href, overview_level=4).squeeze()\n",
    "img = ds.plot(cmap=\"Blues\", add_colorbar=False)\n",
    "img.axes.set_axis_off();"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "d3c08641-fbb6-425f-a3ca-975ca1d425a4",
    "metadata": {},
    "source": [
    "If you wish to work with multiple STAC items as a datacube, you can use libraries like [stackstac](https://stackstac.readthedocs.io/) or [odc-stac](https://odc-stac.readthedocs.io/en/latest/index.html)."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 12,
    "id": "d4a749a5-4a05-405b-8c81-9c10317c9e33",
    "metadata": {},
    "outputs": [
    {
    "data": {
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    "}\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",
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    "}\n",
    "\n",
    ".xr-header > div,\n",
    ".xr-header > ul {\n",
    "  display: inline;\n",
    "  margin-top: 0;\n",
    "  margin-bottom: 0;\n",
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    "\n",
    ".xr-obj-type,\n",
    ".xr-array-name {\n",
    "  margin-left: 2px;\n",
    "  margin-right: 10px;\n",
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    "\n",
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    "  color: var(--xr-font-color2);\n",
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    "\n",
    ".xr-sections {\n",
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    "  display: grid;\n",
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    ".xr-section-item {\n",
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    "\n",
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    "\n",
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    ".xr-section-item input:enabled + label {\n",
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    "\n",
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    "  color: var(--xr-font-color0);\n",
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    "\n",
    ".xr-section-summary {\n",
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    "\n",
    ".xr-section-summary > span {\n",
    "  display: inline-block;\n",
    "  padding-left: 0.5em;\n",
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    "\n",
    ".xr-section-summary-in:disabled + label {\n",
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    "\n",
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    "\n",
    ".xr-section-summary-in:disabled + label:before {\n",
    "  color: var(--xr-disabled-color);\n",
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    "\n",
    ".xr-section-summary-in:checked + label:before {\n",
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    "\n",
    ".xr-section-summary-in:checked + label > span {\n",
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    "\n",
    ".xr-section-summary,\n",
    ".xr-section-inline-details {\n",
    "  padding-top: 4px;\n",
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    "\n",
    ".xr-section-inline-details {\n",
    "  grid-column: 2 / -1;\n",
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    "\n",
    ".xr-section-details {\n",
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    ".xr-preview {\n",
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    "\n",
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    "\n",
    ".xr-array-in:checked ~ .xr-array-data,\n",
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    "\n",
    ".xr-dim-list:after {\n",
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    "\n",
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    "\n",
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    "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;stackstac-6a76bcf3889fe96912bc723182731111&#x27; (time: 4,\n",
    "                                                                band: 19,\n",
    "                                                                y: 7972,\n",
    "                                                                x: 11722)&gt;\n",
    "dask.array&lt;fetch_raster_window, shape=(4, 19, 7972, 11722), dtype=float64, chunksize=(1, 1, 1024, 1024), chunktype=numpy.ndarray&gt;\n",
    "Coordinates: (12/27)\n",
    "  * time                         (time) datetime64[ns] 2020-12-04T19:02:11.19...\n",
    "    id                           (time) &lt;U31 &#x27;LC08_L2SP_047027_20201204_02_T1...\n",
    "  * band                         (band) &lt;U13 &#x27;SR_B1&#x27; &#x27;SR_B2&#x27; ... &#x27;SR_QA_AEROSOL&#x27;\n",
    "  * x                            (x) float64 3.534e+05 3.534e+05 ... 7.05e+05\n",
    "  * y                            (y) float64 5.374e+06 5.374e+06 ... 5.135e+06\n",
    "    view:off_nadir               int64 0\n",
    "    ...                           ...\n",
    "    title                        (band) &lt;U46 &#x27;Coastal/Aerosol Band (B1)&#x27; ... ...\n",
    "    gsd                          (band) float64 30.0 30.0 30.0 ... 30.0 30.0\n",
    "    common_name                  (band) object &#x27;coastal&#x27; &#x27;blue&#x27; ... None None\n",
    "    center_wavelength            (band) object 0.44 0.48 0.56 ... None None None\n",
    "    full_width_half_max          (band) object 0.02 0.06 0.06 ... None None None\n",
    "    epsg                         int64 32610\n",
    "Attributes:\n",
    "    spec:        RasterSpec(epsg=32610, bounds=(353370.0, 5135070.0, 705030.0...\n",
    "    crs:         epsg:32610\n",
    "    transform:   | 30.00, 0.00, 353370.00|\\n| 0.00,-30.00, 5374230.00|\\n| 0.0...\n",
    "    resolution:  30.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'stackstac-6a76bcf3889fe96912bc723182731111'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4</li><li><span class='xr-has-index'>band</span>: 19</li><li><span class='xr-has-index'>y</span>: 7972</li><li><span class='xr-has-index'>x</span>: 11722</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3b404f0e-236f-46e2-a372-761794c2ed5c' class='xr-array-in' type='checkbox' checked><label for='section-3b404f0e-236f-46e2-a372-761794c2ed5c' 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",
    "    <tr>\n",
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    "                </thead>\n",
    "                <tbody>\n",
    "                    \n",
    "                    <tr>\n",
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    "                        <td> 8.00 MiB </td>\n",
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    "  <line x1=\"109\" y1=\"25\" x2=\"229\" y2=\"25\" />\n",
    "  <line x1=\"109\" y1=\"35\" x2=\"229\" y2=\"35\" />\n",
    "  <line x1=\"109\" y1=\"46\" x2=\"229\" y2=\"46\" />\n",
    "  <line x1=\"109\" y1=\"56\" x2=\"229\" y2=\"56\" />\n",
    "  <line x1=\"109\" y1=\"67\" x2=\"229\" y2=\"67\" />\n",
    "  <line x1=\"109\" y1=\"77\" x2=\"229\" y2=\"77\" />\n",
    "  <line x1=\"109\" y1=\"88\" x2=\"229\" y2=\"88\" />\n",
    "  <line x1=\"109\" y1=\"96\" x2=\"229\" y2=\"96\" style=\"stroke-width:2\" />\n",
    "\n",
    "  <!-- Vertical lines -->\n",
    "  <line x1=\"109\" y1=\"14\" x2=\"109\" y2=\"96\" style=\"stroke-width:2\" />\n",
    "  <line x1=\"120\" y1=\"14\" x2=\"120\" y2=\"96\" />\n",
    "  <line x1=\"130\" y1=\"14\" x2=\"130\" y2=\"96\" />\n",
    "  <line x1=\"141\" y1=\"14\" x2=\"141\" y2=\"96\" />\n",
    "  <line x1=\"151\" y1=\"14\" x2=\"151\" y2=\"96\" />\n",
    "  <line x1=\"162\" y1=\"14\" x2=\"162\" y2=\"96\" />\n",
    "  <line x1=\"172\" y1=\"14\" x2=\"172\" y2=\"96\" />\n",
    "  <line x1=\"183\" y1=\"14\" x2=\"183\" y2=\"96\" />\n",
    "  <line x1=\"193\" y1=\"14\" x2=\"193\" y2=\"96\" />\n",
    "  <line x1=\"204\" y1=\"14\" x2=\"204\" y2=\"96\" />\n",
    "  <line x1=\"214\" y1=\"14\" x2=\"214\" y2=\"96\" />\n",
    "  <line x1=\"225\" y1=\"14\" x2=\"225\" y2=\"96\" />\n",
    "  <line x1=\"229\" y1=\"14\" x2=\"229\" y2=\"96\" style=\"stroke-width:2\" />\n",
    "\n",
    "  <!-- Colored Rectangle -->\n",
    "  <polygon points=\"109.9485979497544,14.948597949754403 229.9485979497544,14.948597949754403 229.9485979497544,96.55924459708422 109.9485979497544,96.55924459708422\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
    "\n",
    "  <!-- Text -->\n",
    "  <text x=\"169.948598\" y=\"116.559245\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >11722</text>\n",
    "  <text x=\"249.948598\" y=\"55.753921\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,249.948598,55.753921)\">7972</text>\n",
    "  <text x=\"92.474299\" y=\"109.084946\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,92.474299,109.084946)\">19</text>\n",
    "</svg>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table></div></div></li><li class='xr-section-item'><input id='section-07e07037-b523-454e-af73-a2ba9859cdb1' class='xr-section-summary-in' type='checkbox'  ><label for='section-07e07037-b523-454e-af73-a2ba9859cdb1' class='xr-section-summary' >Coordinates: <span>(27)</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'>2020-12-04T19:02:11.194486 ... 2...</div><input id='attrs-76f8bb4f-0dae-4db1-b785-2d68be389bbb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76f8bb4f-0dae-4db1-b785-2d68be389bbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6efbf31-8d48-44e9-b5d3-d0538826bba9' class='xr-var-data-in' type='checkbox'><label for='data-a6efbf31-8d48-44e9-b5d3-d0538826bba9' 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;2020-12-04T19:02:11.194486000&#x27;, &#x27;2020-12-13T18:56:00.096447000&#x27;,\n",
    "       &#x27;2020-12-20T19:02:09.878796000&#x27;, &#x27;2020-12-29T18:55:56.738265000&#x27;],\n",
    "      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;U31</div><div class='xr-var-preview xr-preview'>&#x27;LC08_L2SP_047027_20201204_02_T1...</div><input id='attrs-8b0c0d59-4f9a-4b54-8b97-54d15280a66d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8b0c0d59-4f9a-4b54-8b97-54d15280a66d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ea35422-a170-4b67-9abd-20c7263355aa' class='xr-var-data-in' type='checkbox'><label for='data-2ea35422-a170-4b67-9abd-20c7263355aa' 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;LC08_L2SP_047027_20201204_02_T1&#x27;,\n",
    "       &#x27;LC08_L2SP_046027_20201213_02_T2&#x27;,\n",
    "       &#x27;LC08_L2SP_047027_20201220_02_T2&#x27;,\n",
    "       &#x27;LC08_L2SP_046027_20201229_02_T2&#x27;], dtype=&#x27;&lt;U31&#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;U13</div><div class='xr-var-preview xr-preview'>&#x27;SR_B1&#x27; &#x27;SR_B2&#x27; ... &#x27;SR_QA_AEROSOL&#x27;</div><input id='attrs-4a9668db-f571-4ad3-a3f5-47b8e6430675' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a9668db-f571-4ad3-a3f5-47b8e6430675' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baa7847e-4dff-40cb-8e3f-e1361dc07709' class='xr-var-data-in' type='checkbox'><label for='data-baa7847e-4dff-40cb-8e3f-e1361dc07709' 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;SR_B1&#x27;, &#x27;SR_B2&#x27;, &#x27;SR_B3&#x27;, &#x27;SR_B4&#x27;, &#x27;SR_B5&#x27;, &#x27;SR_B6&#x27;, &#x27;SR_B7&#x27;, &#x27;ST_QA&#x27;,\n",
    "       &#x27;ST_B10&#x27;, &#x27;ST_DRAD&#x27;, &#x27;ST_EMIS&#x27;, &#x27;ST_EMSD&#x27;, &#x27;ST_TRAD&#x27;, &#x27;ST_URAD&#x27;,\n",
    "       &#x27;QA_PIXEL&#x27;, &#x27;ST_ATRAN&#x27;, &#x27;ST_CDIST&#x27;, &#x27;QA_RADSAT&#x27;, &#x27;SR_QA_AEROSOL&#x27;],\n",
    "      dtype=&#x27;&lt;U13&#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'>3.534e+05 3.534e+05 ... 7.05e+05</div><input id='attrs-de8f64fe-ded8-40aa-99a4-5cf764730c9c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de8f64fe-ded8-40aa-99a4-5cf764730c9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10604a32-17cf-4873-890d-83c073878f71' class='xr-var-data-in' type='checkbox'><label for='data-10604a32-17cf-4873-890d-83c073878f71' 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([353370., 353400., 353430., ..., 704940., 704970., 705000.])</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'>5.374e+06 5.374e+06 ... 5.135e+06</div><input id='attrs-c3d40456-76be-4942-8d74-41451744bc25' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c3d40456-76be-4942-8d74-41451744bc25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84755af2-c9ce-4ddc-80c4-922317e5bf0d' class='xr-var-data-in' type='checkbox'><label for='data-84755af2-c9ce-4ddc-80c4-922317e5bf0d' 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([5374230., 5374200., 5374170., ..., 5135160., 5135130., 5135100.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>view:off_nadir</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-67c2bd6d-8cdf-45eb-989a-297f3620b6aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67c2bd6d-8cdf-45eb-989a-297f3620b6aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20d4a82b-f21f-4c2b-961a-a61e45d8c351' class='xr-var-data-in' type='checkbox'><label for='data-20d4a82b-f21f-4c2b-961a-a61e45d8c351' 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)</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'>32610</div><input id='attrs-8a993d95-7823-48de-ad5e-52d6648e67c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a993d95-7823-48de-ad5e-52d6648e67c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23303d24-b586-4cb5-8ba6-73f1cf03b3a5' class='xr-var-data-in' type='checkbox'><label for='data-23303d24-b586-4cb5-8ba6-73f1cf03b3a5' 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(32610)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>platform</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;landsat-8&#x27;</div><input id='attrs-3747cddb-9eb3-424e-a27a-4171f28c1baf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3747cddb-9eb3-424e-a27a-4171f28c1baf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aed22ad7-fdef-4757-99aa-72660c2c85c1' class='xr-var-data-in' type='checkbox'><label for='data-aed22ad7-fdef-4757-99aa-72660c2c85c1' 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;landsat-8&#x27;, dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:wrs_row</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;027&#x27;</div><input id='attrs-f0360891-be93-401c-9eab-dcd16679c05c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f0360891-be93-401c-9eab-dcd16679c05c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0802c21e-4c52-480a-b6cf-9c796667959b' class='xr-var-data-in' type='checkbox'><label for='data-0802c21e-4c52-480a-b6cf-9c796667959b' 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;027&#x27;, dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:wrs_path</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;047&#x27; &#x27;046&#x27; &#x27;047&#x27; &#x27;046&#x27;</div><input id='attrs-2311ef46-8614-49eb-901f-c5adf8fbbc8f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2311ef46-8614-49eb-901f-c5adf8fbbc8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-faad6f82-3bb5-4ad7-938b-095f5984e5f1' class='xr-var-data-in' type='checkbox'><label for='data-faad6f82-3bb5-4ad7-938b-095f5984e5f1' 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;047&#x27;, &#x27;046&#x27;, &#x27;047&#x27;, &#x27;046&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:collection_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;02&#x27;</div><input id='attrs-e96c8f1e-39c1-45ec-bbb6-39becc510cdd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e96c8f1e-39c1-45ec-bbb6-39becc510cdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc6fb7ec-94bb-43bb-8b98-4efd38686dab' class='xr-var-data-in' type='checkbox'><label for='data-dc6fb7ec-94bb-43bb-8b98-4efd38686dab' 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;02&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:cloud_cover_land</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.9 98.64 100.0 100.0</div><input id='attrs-4e380070-1c22-447c-a80f-6a10e69e85f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e380070-1c22-447c-a80f-6a10e69e85f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb134c8c-d055-4165-ad5c-7d3c089c7750' class='xr-var-data-in' type='checkbox'><label for='data-eb134c8c-d055-4165-ad5c-7d3c089c7750' 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([  1.9 ,  98.64, 100.  , 100.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>view:sun_elevation</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.81 17.8 17.41 17.46</div><input id='attrs-5652e771-d871-42a1-b0e7-02aa8fabc3dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5652e771-d871-42a1-b0e7-02aa8fabc3dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dce9c54a-a176-4e00-9784-b89c157c2143' class='xr-var-data-in' type='checkbox'><label for='data-dce9c54a-a176-4e00-9784-b89c157c2143' 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([18.80722985, 17.7997438 , 17.41444102, 17.45829837])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:collection_category</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;T1&#x27; &#x27;T2&#x27; &#x27;T2&#x27; &#x27;T2&#x27;</div><input id='attrs-01e7a779-2a3d-4fe7-8204-d84cc6c5a06b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01e7a779-2a3d-4fe7-8204-d84cc6c5a06b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a592425-9c21-4a33-9677-3019ef6fde01' class='xr-var-data-in' type='checkbox'><label for='data-0a592425-9c21-4a33-9677-3019ef6fde01' 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;T1&#x27;, &#x27;T2&#x27;, &#x27;T2&#x27;, &#x27;T2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:processing_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;L2SP&#x27;</div><input id='attrs-34ddc81b-7cb9-46f7-8a9b-e1e5f442ab73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34ddc81b-7cb9-46f7-8a9b-e1e5f442ab73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c8a4ed8-3e5b-4847-9f38-f9ee0e33604d' class='xr-var-data-in' type='checkbox'><label for='data-5c8a4ed8-3e5b-4847-9f38-f9ee0e33604d' 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;L2SP&#x27;, dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:wrs_type</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;2&#x27;</div><input id='attrs-8432d390-6e2f-4b30-9ae0-bbb972f49dce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8432d390-6e2f-4b30-9ae0-bbb972f49dce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65871ff2-872e-4ddf-8904-3076d83649bd' class='xr-var-data-in' type='checkbox'><label for='data-65871ff2-872e-4ddf-8904-3076d83649bd' 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;2&#x27;, dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>view:sun_azimuth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>164.9 164.1 163.4 162.3</div><input id='attrs-453cfcd4-164e-4ca4-82fe-aa68852c64e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-453cfcd4-164e-4ca4-82fe-aa68852c64e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aff39f2c-b58b-4504-b668-a372b5f5e91c' class='xr-var-data-in' type='checkbox'><label for='data-aff39f2c-b58b-4504-b668-a372b5f5e91c' 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([164.91405951, 164.12618828, 163.36011782, 162.25323052])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>instruments</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;oli&#x27;, &#x27;tirs&#x27;}</div><input id='attrs-1d020633-b0c0-46a2-a1ca-1a7d566deda0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d020633-b0c0-46a2-a1ca-1a7d566deda0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-397570fb-2d2f-4ff7-bf39-60eb2a1433ef' class='xr-var-data-in' type='checkbox'><label for='data-397570fb-2d2f-4ff7-bf39-60eb2a1433ef' 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;oli&#x27;, &#x27;tirs&#x27;}, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>eo:cloud_cover</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.55 98.73 100.0 100.0</div><input id='attrs-c30c47b1-1e77-409c-85fc-3b5d0d277509' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c30c47b1-1e77-409c-85fc-3b5d0d277509' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-315b374b-401a-445b-a6fe-f27850addcc6' class='xr-var-data-in' type='checkbox'><label for='data-315b374b-401a-445b-a6fe-f27850addcc6' 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([  1.55,  98.73, 100.  , 100.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:scene_id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;LC80470272020339LGN00&#x27; ... &#x27;LC8...</div><input id='attrs-702d81c7-a0bb-413d-8eb4-364ca99bbab3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-702d81c7-a0bb-413d-8eb4-364ca99bbab3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19581b55-d017-40f5-be97-d6beca8b9f42' class='xr-var-data-in' type='checkbox'><label for='data-19581b55-d017-40f5-be97-d6beca8b9f42' 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;LC80470272020339LGN00&#x27;, &#x27;LC80460272020348LGN00&#x27;,\n",
    "       &#x27;LC80470272020355LGN00&#x27;, &#x27;LC80460272020364LGN00&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>description</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U91</div><div class='xr-var-preview xr-preview'>&#x27;Collection 2 Level-2 Coastal/Ae...</div><input id='attrs-b3c6113f-7740-432d-8370-5af0e04898db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3c6113f-7740-432d-8370-5af0e04898db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61c1b488-cfc6-447e-8ef2-9c51fd7202c7' class='xr-var-data-in' type='checkbox'><label for='data-61c1b488-cfc6-447e-8ef2-9c51fd7202c7' 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;Collection 2 Level-2 Coastal/Aerosol Band (B1) Surface Reflectance&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Blue Band (B2) Surface Reflectance&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Green Band (B3) Surface Reflectance&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Red Band (B4) Surface Reflectance&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Near Infrared Band 0.8 (B5) Surface Reflectance&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Short-wave Infrared Band 1.6 (B6) Surface Reflectance&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Short-wave Infrared Band 2.2 (B7) Surface Reflectance&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Surface Temperature Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Surface Temperature Band (B10) Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Downwelled Radiance Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Emissivity Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Emissivity Standard Deviation Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Thermal Radiance Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Upwelled Radiance Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Collection 2 Level-1 Pixel Quality Assessment Band&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Atmospheric Transmittance Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Landsat Collection 2 Level-2 Cloud Distance Band Surface Temperature Product&#x27;,\n",
    "       &#x27;Collection 2 Level-1 Radiometric Saturation Quality Assessment Band&#x27;,\n",
    "       &#x27;Collection 2 Level-2 Aerosol Quality Analysis Band (ANG) Surface Reflectance&#x27;],\n",
    "      dtype=&#x27;&lt;U91&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>title</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U46</div><div class='xr-var-preview xr-preview'>&#x27;Coastal/Aerosol Band (B1)&#x27; ... ...</div><input id='attrs-1ece66da-a033-414f-89c9-470bd4592662' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ece66da-a033-414f-89c9-470bd4592662' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-047df493-70dd-41b5-9b49-dd2980ccae1b' class='xr-var-data-in' type='checkbox'><label for='data-047df493-70dd-41b5-9b49-dd2980ccae1b' 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;Coastal/Aerosol Band (B1)&#x27;, &#x27;Blue Band (B2)&#x27;, &#x27;Green Band (B3)&#x27;,\n",
    "       &#x27;Red Band (B4)&#x27;, &#x27;Near Infrared Band 0.8 (B5)&#x27;,\n",
    "       &#x27;Short-wave Infrared Band 1.6 (B6)&#x27;,\n",
    "       &#x27;Short-wave Infrared Band 2.2 (B7)&#x27;,\n",
    "       &#x27;Surface Temperature Quality Assessment Band&#x27;,\n",
    "       &#x27;Surface Temperature Band (B10)&#x27;, &#x27;Downwelled Radiance Band&#x27;,\n",
    "       &#x27;Emissivity Band&#x27;, &#x27;Emissivity Standard Deviation Band&#x27;,\n",
    "       &#x27;Thermal Radiance Band&#x27;, &#x27;Upwelled Radiance Band&#x27;,\n",
    "       &#x27;Pixel Quality Assessment Band&#x27;, &#x27;Atmospheric Transmittance Band&#x27;,\n",
    "       &#x27;Cloud Distance Band&#x27;,\n",
    "       &#x27;Radiometric Saturation Quality Assessment Band&#x27;,\n",
    "       &#x27;Aerosol Quality Analysis Band&#x27;], dtype=&#x27;&lt;U46&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gsd</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 30.0 30.0 ... 30.0 30.0 30.0</div><input id='attrs-18ec3ef7-b3be-4d23-8dfd-cbd570208fc6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-18ec3ef7-b3be-4d23-8dfd-cbd570208fc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1abd55f4-8f5f-4d41-9af3-91c37fffeb2f' class='xr-var-data-in' type='checkbox'><label for='data-1abd55f4-8f5f-4d41-9af3-91c37fffeb2f' 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([ 30.,  30.,  30.,  30.,  30.,  30.,  30.,  30., 100.,  30.,  30.,\n",
    "        30.,  30.,  30.,  30.,  30.,  30.,  30.,  30.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>common_name</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;coastal&#x27; &#x27;blue&#x27; ... None None</div><input id='attrs-c887cfe7-9127-439f-b10f-97a7721caede' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c887cfe7-9127-439f-b10f-97a7721caede' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b05db78-b47f-4aed-92c9-56cd75a9476d' class='xr-var-data-in' type='checkbox'><label for='data-8b05db78-b47f-4aed-92c9-56cd75a9476d' 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;coastal&#x27;, &#x27;blue&#x27;, &#x27;green&#x27;, &#x27;red&#x27;, &#x27;nir08&#x27;, &#x27;swir16&#x27;, &#x27;swir22&#x27;,\n",
    "       None, &#x27;lwir11&#x27;, None, None, None, None, None, None, None, None,\n",
    "       None, None], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>center_wavelength</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0.44 0.48 0.56 ... None None None</div><input id='attrs-f7da6ab5-af1d-4b5f-832d-05404efde1d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7da6ab5-af1d-4b5f-832d-05404efde1d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-788a9a82-4b1c-4c5b-8680-703547b4cba8' class='xr-var-data-in' type='checkbox'><label for='data-788a9a82-4b1c-4c5b-8680-703547b4cba8' 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([0.44, 0.48, 0.56, 0.65, 0.86, 1.6, 2.2, None, 10.9, None, None,\n",
    "       None, None, None, None, None, None, None, None], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>full_width_half_max</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0.02 0.06 0.06 ... None None None</div><input id='attrs-53cb251a-90d4-4b1b-abb1-e06738a578b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53cb251a-90d4-4b1b-abb1-e06738a578b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4e45d70-9140-4612-b694-919c6f5e8fdb' class='xr-var-data-in' type='checkbox'><label for='data-f4e45d70-9140-4612-b694-919c6f5e8fdb' 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([0.02, 0.06, 0.06, 0.04, 0.03, 0.08, 0.2, None, 0.8, None, None,\n",
    "       None, None, None, None, None, None, None, None], 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'>32610</div><input id='attrs-5526c7bb-fbf2-44bf-996c-29da26ca8d18' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5526c7bb-fbf2-44bf-996c-29da26ca8d18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc686fc3-f4e6-4eae-8320-fc0a9647316f' class='xr-var-data-in' type='checkbox'><label for='data-dc686fc3-f4e6-4eae-8320-fc0a9647316f' 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(32610)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63ddeb6e-e9b4-494f-baed-ce6436956a26' class='xr-section-summary-in' type='checkbox'  checked><label for='section-63ddeb6e-e9b4-494f-baed-ce6436956a26' 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=32610, bounds=(353370.0, 5135070.0, 705030.0, 5374230.0), resolutions_xy=(30.0, 30.0))</dd><dt><span>crs :</span></dt><dd>epsg:32610</dd><dt><span>transform :</span></dt><dd>| 30.00, 0.00, 353370.00|\n",
    "| 0.00,-30.00, 5374230.00|\n",
    "| 0.00, 0.00, 1.00|</dd><dt><span>resolution :</span></dt><dd>30.0</dd></dl></div></li></ul></div></div>"
    ],
    "text/plain": [
    "<xarray.DataArray 'stackstac-6a76bcf3889fe96912bc723182731111' (time: 4,\n",
    "                                                                band: 19,\n",
    "                                                                y: 7972,\n",
    "                                                                x: 11722)>\n",
    "dask.array<fetch_raster_window, shape=(4, 19, 7972, 11722), dtype=float64, chunksize=(1, 1, 1024, 1024), chunktype=numpy.ndarray>\n",
    "Coordinates: (12/27)\n",
    "  * time                         (time) datetime64[ns] 2020-12-04T19:02:11.19...\n",
    "    id                           (time) <U31 'LC08_L2SP_047027_20201204_02_T1...\n",
    "  * band                         (band) <U13 'SR_B1' 'SR_B2' ... 'SR_QA_AEROSOL'\n",
    "  * x                            (x) float64 3.534e+05 3.534e+05 ... 7.05e+05\n",
    "  * y                            (y) float64 5.374e+06 5.374e+06 ... 5.135e+06\n",
    "    view:off_nadir               int64 0\n",
    "    ...                           ...\n",
    "    title                        (band) <U46 'Coastal/Aerosol Band (B1)' ... ...\n",
    "    gsd                          (band) float64 30.0 30.0 30.0 ... 30.0 30.0\n",
    "    common_name                  (band) object 'coastal' 'blue' ... None None\n",
    "    center_wavelength            (band) object 0.44 0.48 0.56 ... None None None\n",
    "    full_width_half_max          (band) object 0.02 0.06 0.06 ... None None None\n",
    "    epsg                         int64 32610\n",
    "Attributes:\n",
    "    spec:        RasterSpec(epsg=32610, bounds=(353370.0, 5135070.0, 705030.0...\n",
    "    crs:         epsg:32610\n",
    "    transform:   | 30.00, 0.00, 353370.00|\\n| 0.00,-30.00, 5374230.00|\\n| 0.0...\n",
    "    resolution:  30.0"
    ]
    },
    "execution_count": 12,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "import stackstac\n",
    "\n",
    "ds = stackstac.stack(planetary_computer.sign(items))\n",
    "ds"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "fc96240e-edb9-4e6d-9c70-645d91813a7f",
    "metadata": {},
    "source": [
    "### Searching on additional properties\n",
    "\n",
    "Previously, we searched for items by space and time. Because the Planetary Computer's STAC API supports the [query](https://github.com/radiantearth/stac-api-spec/blob/master/fragments/query/README.md) parameter, you can search on additional properties on the STAC item.\n",
    "\n",
    "For example, collections like `sentinel-2-l2a` and `landsat-8-c2-l2` both implement the [`eo` STAC extension](https://github.com/stac-extensions/eo) and include an `eo:cloud_cover` property. Use `query={\"eo:cloud_cover\": {\"lt\": 20}}` to return only items that are less than 20% cloudy."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 13,
    "id": "18c2f286-654a-479a-9ae0-0f819250b575",
    "metadata": {},
    "outputs": [],
    "source": [
    "time_range = \"2020-12-01/2020-12-31\"\n",
    "bbox = [-122.2751, 47.5469, -121.9613, 47.7458]\n",
    "\n",
    "search = catalog.search(\n",
    "    collections=[\"sentinel-2-l2a\"],\n",
    "    bbox=bbox,\n",
    "    datetime=time_range,\n",
    "    query={\"eo:cloud_cover\": {\"lt\": 20}},\n",
    ")\n",
    "items = search.get_all_items()"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "fda18a4d-7421-420b-a918-c45ce43833a9",
    "metadata": {},
    "source": [
    "Other common uses of the `query` parameter is to filter a collection down to items of a specific type, For example, the [GOES-CMI](https://planetarycomputer.microsoft.com/dataset/goes-cmi) collection includes images from various when the satellite is in various modes, which produces images of either the Full Disk of the earth, the continental United States, or a mesoscale. You can use `goes:image-type` to filter down to just the ones you want."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 14,
    "id": "d2db005e-9732-43e2-89c1-3133a6fda2d1",
    "metadata": {},
    "outputs": [],
    "source": [
    "search = catalog.search(\n",
    "    collections=[\"goes-cmi\"],\n",
    "    bbox=[-67.2729, 25.6000, -61.7999, 27.5423],\n",
    "    datetime=[\"2018-09-11T13:00:00Z\", \"2018-09-11T15:40:00Z\"],\n",
    "    query={\"goes:image-type\": {\"eq\": \"MESOSCALE\"}},\n",
    ")"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "10cb5d51-7d01-4d8b-ad14-1c3df6cea258",
    "metadata": {},
    "source": [
    "### Analyzing STAC Metadata\n",
    "\n",
    "STAC items are proper GeoJSON Features, and so can be treated as a kind of data on their own."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 15,
    "id": "0283b780-d1c8-4715-bcc0-0e533110020f",
    "metadata": {
    "tags": []
    },
    "outputs": [
    {
    "data": {
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    ],
    "text/plain": [
    "<folium.folium.Map at 0x7f558b4e83d0>"
    ]
    },
    "execution_count": 15,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "search = catalog.search(\n",
    "    collections=[\"sentinel-2-l2a\"],\n",
    "    bbox=[-124.2751, 45.5469, -110.9613, 47.7458],\n",
    "    datetime=\"2020-12-26/2020-12-31\",\n",
    ")\n",
    "items = search.get_all_items()\n",
    "\n",
    "df = geopandas.GeoDataFrame.from_features(items.to_dict(), crs=\"epsg:4326\")\n",
    "\n",
    "df[[\"geometry\", \"datetime\", \"s2:mgrs_tile\", \"eo:cloud_cover\"]].explore(\n",
    "    column=\"eo:cloud_cover\", style_kwds={\"fillOpacity\": 0.1}\n",
    ")"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "debaa186-f987-49c0-a476-98835207fd1f",
    "metadata": {},
    "source": [
    "Or we can plot cloudiness of a region over time."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 16,
    "id": "c27178d2-bc51-4097-a5d7-b2e438f61e9e",
    "metadata": {},
    "outputs": [],
    "source": [
    "import pandas as pd\n",
    "\n",
    "search = catalog.search(\n",
    "    collections=[\"sentinel-2-l2a\"],\n",
    "    bbox=[-124.2751, 45.5469, -123.9613, 45.7458],\n",
    "    datetime=\"2020-01-01/2020-12-31\",\n",
    ")\n",
    "items = search.get_all_items()\n",
    "df = geopandas.GeoDataFrame.from_features(items.to_dict())\n",
    "df[\"datetime\"] = pd.to_datetime(df[\"datetime\"])"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 17,
    "id": "07a7e2be-cf30-4cfe-812d-83ab8b436dfe",
    "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": [
    "ts = df.set_index(\"datetime\").sort_index()[\"eo:cloud_cover\"].rolling(7).mean()\n",
    "ts.plot(title=\"eo:cloud-cover (7-scene rolling average)\");"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "13669344-a6c2-4684-ba78-69b7907e37e1",
    "metadata": {},
    "source": [
    "### Working with STAC Catalogs and Collections\n",
    "\n",
    "Our `catalog` is a [STAC Catalog](https://github.com/radiantearth/stac-spec/blob/master/catalog-spec/catalog-spec.md) that we can crawl or search. The Catalog contains [STAC Collections](https://github.com/radiantearth/stac-spec/blob/master/collection-spec/collection-spec.md) for each dataset we have indexed (which is not the yet the entirity of data hosted by the Planetary Computer).\n",
    "\n",
    "Collections have information about the [STAC Items](https://github.com/radiantearth/stac-spec/blob/master/item-spec/item-spec.md) they contain. For instance, here we look at the [Bands](https://github.com/stac-extensions/eo#band-object) available for [Landsat 8 Collection 2 Level 2](https://planetarycomputer.microsoft.com/dataset/landsat-8-c2-l2) data:"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 18,
    "id": "8da11d26-3658-4b9e-b790-f84a2aded3e8",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/html": [
    "<div>\n",
    "<style scoped>\n",
    "    .dataframe tbody tr th:only-of-type {\n",
    "        vertical-align: middle;\n",
    "    }\n",
    "\n",
    "    .dataframe tbody tr th {\n",
    "        vertical-align: top;\n",
    "    }\n",
    "\n",
    "    .dataframe thead th {\n",
    "        text-align: right;\n",
    "    }\n",
    "</style>\n",
    "<table border=\"1\" class=\"dataframe\">\n",
    "  <thead>\n",
    "    <tr style=\"text-align: right;\">\n",
    "      <th></th>\n",
    "      <th>gsd</th>\n",
    "      <th>name</th>\n",
    "      <th>common_name</th>\n",
    "      <th>description</th>\n",
    "      <th>center_wavelength</th>\n",
    "      <th>full_width_half_max</th>\n",
    "    </tr>\n",
    "  </thead>\n",
    "  <tbody>\n",
    "    <tr>\n",
    "      <th>0</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B1</td>\n",
    "      <td>coastal</td>\n",
    "      <td>coastal</td>\n",
    "      <td>0.44</td>\n",
    "      <td>0.02</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>1</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B2</td>\n",
    "      <td>blue</td>\n",
    "      <td>visible blue</td>\n",
    "      <td>0.48</td>\n",
    "      <td>0.06</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>2</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B3</td>\n",
    "      <td>green</td>\n",
    "      <td>visible green</td>\n",
    "      <td>0.56</td>\n",
    "      <td>0.06</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>3</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B4</td>\n",
    "      <td>red</td>\n",
    "      <td>visible red</td>\n",
    "      <td>0.65</td>\n",
    "      <td>0.04</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>4</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B5</td>\n",
    "      <td>nir</td>\n",
    "      <td>near-infrared</td>\n",
    "      <td>0.86</td>\n",
    "      <td>0.03</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>5</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B6</td>\n",
    "      <td>swir16</td>\n",
    "      <td>short-wave infrared</td>\n",
    "      <td>1.60</td>\n",
    "      <td>0.08</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>6</th>\n",
    "      <td>30</td>\n",
    "      <td>SR_B7</td>\n",
    "      <td>swir22</td>\n",
    "      <td>short-wave infrared</td>\n",
    "      <td>2.20</td>\n",
    "      <td>0.20</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>7</th>\n",
    "      <td>100</td>\n",
    "      <td>ST_B10</td>\n",
    "      <td>lwir11</td>\n",
    "      <td>long-wave infrared</td>\n",
    "      <td>10.90</td>\n",
    "      <td>0.80</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>8</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_TRAD</td>\n",
    "      <td>NaN</td>\n",
    "      <td>thermal radiance</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>9</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_URAD</td>\n",
    "      <td>NaN</td>\n",
    "      <td>upwelled radiance</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>10</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_ATRAN</td>\n",
    "      <td>NaN</td>\n",
    "      <td>atmospheric transmission</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>11</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_CDIST</td>\n",
    "      <td>NaN</td>\n",
    "      <td>distance to nearest cloud</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>12</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_DRAD</td>\n",
    "      <td>NaN</td>\n",
    "      <td>downwelled radiance</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>13</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_EMIS</td>\n",
    "      <td>NaN</td>\n",
    "      <td>emissivity</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>14</th>\n",
    "      <td>30</td>\n",
    "      <td>ST_EMSD</td>\n",
    "      <td>NaN</td>\n",
    "      <td>emissivity standard deviation</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "  </tbody>\n",
    "</table>\n",
    "</div>"
    ],
    "text/plain": [
    "    gsd      name common_name                    description  \\\n",
    "0    30     SR_B1     coastal                        coastal   \n",
    "1    30     SR_B2        blue                   visible blue   \n",
    "2    30     SR_B3       green                  visible green   \n",
    "3    30     SR_B4         red                    visible red   \n",
    "4    30     SR_B5         nir                  near-infrared   \n",
    "5    30     SR_B6      swir16            short-wave infrared   \n",
    "6    30     SR_B7      swir22            short-wave infrared   \n",
    "7   100    ST_B10      lwir11             long-wave infrared   \n",
    "8    30   ST_TRAD         NaN               thermal radiance   \n",
    "9    30   ST_URAD         NaN              upwelled radiance   \n",
    "10   30  ST_ATRAN         NaN       atmospheric transmission   \n",
    "11   30  ST_CDIST         NaN      distance to nearest cloud   \n",
    "12   30   ST_DRAD         NaN            downwelled radiance   \n",
    "13   30   ST_EMIS         NaN                     emissivity   \n",
    "14   30   ST_EMSD         NaN  emissivity standard deviation   \n",
    "\n",
    "    center_wavelength  full_width_half_max  \n",
    "0                0.44                 0.02  \n",
    "1                0.48                 0.06  \n",
    "2                0.56                 0.06  \n",
    "3                0.65                 0.04  \n",
    "4                0.86                 0.03  \n",
    "5                1.60                 0.08  \n",
    "6                2.20                 0.20  \n",
    "7               10.90                 0.80  \n",
    "8                 NaN                  NaN  \n",
    "9                 NaN                  NaN  \n",
    "10                NaN                  NaN  \n",
    "11                NaN                  NaN  \n",
    "12                NaN                  NaN  \n",
    "13                NaN                  NaN  \n",
    "14                NaN                  NaN  "
    ]
    },
    "execution_count": 18,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "import pandas as pd\n",
    "\n",
    "landsat = catalog.get_collection(\"landsat-8-c2-l2\")\n",
    "\n",
    "pd.DataFrame(landsat.extra_fields[\"summaries\"][\"eo:bands\"])"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "4ae651c0",
    "metadata": {},
    "source": [
    "We can see what [Assets](https://github.com/radiantearth/stac-spec/blob/master/item-spec/item-spec.md#asset-object) are available on our item with:"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 19,
    "id": "4bb2b985-f18d-4161-9331-b4b259814f34",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/html": [
    "<div>\n",
    "<style scoped>\n",
    "    .dataframe tbody tr th:only-of-type {\n",
    "        vertical-align: middle;\n",
    "    }\n",
    "\n",
    "    .dataframe tbody tr th {\n",
    "        vertical-align: top;\n",
    "    }\n",
    "\n",
    "    .dataframe thead th {\n",
    "        text-align: right;\n",
    "    }\n",
    "</style>\n",
    "<table border=\"1\" class=\"dataframe\">\n",
    "  <thead>\n",
    "    <tr style=\"text-align: right;\">\n",
    "      <th></th>\n",
    "      <th>title</th>\n",
    "      <th>description</th>\n",
    "      <th>gsd</th>\n",
    "    </tr>\n",
    "  </thead>\n",
    "  <tbody>\n",
    "    <tr>\n",
    "      <th>ANG</th>\n",
    "      <td>Angle Coefficients File</td>\n",
    "      <td>Collection 2 Level-1 Angle Coefficients File (...</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B1</th>\n",
    "      <td>Coastal/Aerosol Band (B1)</td>\n",
    "      <td>Collection 2 Level-2 Coastal/Aerosol Band (B1)...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B2</th>\n",
    "      <td>Blue Band (B2)</td>\n",
    "      <td>Collection 2 Level-2 Blue Band (B2) Surface Re...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B3</th>\n",
    "      <td>Green Band (B3)</td>\n",
    "      <td>Collection 2 Level-2 Green Band (B3) Surface R...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B4</th>\n",
    "      <td>Red Band (B4)</td>\n",
    "      <td>Collection 2 Level-2 Red Band (B4) Surface Ref...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B5</th>\n",
    "      <td>Near Infrared Band 0.8 (B5)</td>\n",
    "      <td>Collection 2 Level-2 Near Infrared Band 0.8 (B...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B6</th>\n",
    "      <td>Short-wave Infrared Band 1.6 (B6)</td>\n",
    "      <td>Collection 2 Level-2 Short-wave Infrared Band ...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_B7</th>\n",
    "      <td>Short-wave Infrared Band 2.2 (B7)</td>\n",
    "      <td>Collection 2 Level-2 Short-wave Infrared Band ...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_QA</th>\n",
    "      <td>Surface Temperature Quality Assessment Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Surface Temperatu...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_B10</th>\n",
    "      <td>Surface Temperature Band (B10)</td>\n",
    "      <td>Landsat Collection 2 Level-2 Surface Temperatu...</td>\n",
    "      <td>100.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>MTL.txt</th>\n",
    "      <td>Product Metadata File</td>\n",
    "      <td>Collection 2 Level-1 Product Metadata File (MTL)</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>MTL.xml</th>\n",
    "      <td>Product Metadata File (xml)</td>\n",
    "      <td>Collection 2 Level-1 Product Metadata File (xml)</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_DRAD</th>\n",
    "      <td>Downwelled Radiance Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Downwelled Radian...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_EMIS</th>\n",
    "      <td>Emissivity Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Emissivity Band S...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_EMSD</th>\n",
    "      <td>Emissivity Standard Deviation Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Emissivity Standa...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_TRAD</th>\n",
    "      <td>Thermal Radiance Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Thermal Radiance ...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_URAD</th>\n",
    "      <td>Upwelled Radiance Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Upwelled Radiance...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>MTL.json</th>\n",
    "      <td>Product Metadata File (json)</td>\n",
    "      <td>Collection 2 Level-1 Product Metadata File (json)</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>QA_PIXEL</th>\n",
    "      <td>Pixel Quality Assessment Band</td>\n",
    "      <td>Collection 2 Level-1 Pixel Quality Assessment ...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_ATRAN</th>\n",
    "      <td>Atmospheric Transmittance Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Atmospheric Trans...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>ST_CDIST</th>\n",
    "      <td>Cloud Distance Band</td>\n",
    "      <td>Landsat Collection 2 Level-2 Cloud Distance Ba...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>QA_RADSAT</th>\n",
    "      <td>Radiometric Saturation Quality Assessment Band</td>\n",
    "      <td>Collection 2 Level-1 Radiometric Saturation Qu...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>thumbnail</th>\n",
    "      <td>Thumbnail image</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>SR_QA_AEROSOL</th>\n",
    "      <td>Aerosol Quality Analysis Band</td>\n",
    "      <td>Collection 2 Level-2 Aerosol Quality Analysis ...</td>\n",
    "      <td>30.0</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <th>reduced_resolution_browse</th>\n",
    "      <td>Reduced resolution browse image</td>\n",
    "      <td>NaN</td>\n",
    "      <td>NaN</td>\n",
    "    </tr>\n",
    "  </tbody>\n",
    "</table>\n",
    "</div>"
    ],
    "text/plain": [
    "                                                                    title  \\\n",
    "ANG                                               Angle Coefficients File   \n",
    "SR_B1                                           Coastal/Aerosol Band (B1)   \n",
    "SR_B2                                                      Blue Band (B2)   \n",
    "SR_B3                                                     Green Band (B3)   \n",
    "SR_B4                                                       Red Band (B4)   \n",
    "SR_B5                                         Near Infrared Band 0.8 (B5)   \n",
    "SR_B6                                   Short-wave Infrared Band 1.6 (B6)   \n",
    "SR_B7                                   Short-wave Infrared Band 2.2 (B7)   \n",
    "ST_QA                         Surface Temperature Quality Assessment Band   \n",
    "ST_B10                                     Surface Temperature Band (B10)   \n",
    "MTL.txt                                             Product Metadata File   \n",
    "MTL.xml                                       Product Metadata File (xml)   \n",
    "ST_DRAD                                          Downwelled Radiance Band   \n",
    "ST_EMIS                                                   Emissivity Band   \n",
    "ST_EMSD                                Emissivity Standard Deviation Band   \n",
    "ST_TRAD                                             Thermal Radiance Band   \n",
    "ST_URAD                                            Upwelled Radiance Band   \n",
    "MTL.json                                     Product Metadata File (json)   \n",
    "QA_PIXEL                                    Pixel Quality Assessment Band   \n",
    "ST_ATRAN                                   Atmospheric Transmittance Band   \n",
    "ST_CDIST                                              Cloud Distance Band   \n",
    "QA_RADSAT                  Radiometric Saturation Quality Assessment Band   \n",
    "thumbnail                                                 Thumbnail image   \n",
    "SR_QA_AEROSOL                               Aerosol Quality Analysis Band   \n",
    "reduced_resolution_browse                 Reduced resolution browse image   \n",
    "\n",
    "                                                                 description  \\\n",
    "ANG                        Collection 2 Level-1 Angle Coefficients File (...   \n",
    "SR_B1                      Collection 2 Level-2 Coastal/Aerosol Band (B1)...   \n",
    "SR_B2                      Collection 2 Level-2 Blue Band (B2) Surface Re...   \n",
    "SR_B3                      Collection 2 Level-2 Green Band (B3) Surface R...   \n",
    "SR_B4                      Collection 2 Level-2 Red Band (B4) Surface Ref...   \n",
    "SR_B5                      Collection 2 Level-2 Near Infrared Band 0.8 (B...   \n",
    "SR_B6                      Collection 2 Level-2 Short-wave Infrared Band ...   \n",
    "SR_B7                      Collection 2 Level-2 Short-wave Infrared Band ...   \n",
    "ST_QA                      Landsat Collection 2 Level-2 Surface Temperatu...   \n",
    "ST_B10                     Landsat Collection 2 Level-2 Surface Temperatu...   \n",
    "MTL.txt                     Collection 2 Level-1 Product Metadata File (MTL)   \n",
    "MTL.xml                     Collection 2 Level-1 Product Metadata File (xml)   \n",
    "ST_DRAD                    Landsat Collection 2 Level-2 Downwelled Radian...   \n",
    "ST_EMIS                    Landsat Collection 2 Level-2 Emissivity Band S...   \n",
    "ST_EMSD                    Landsat Collection 2 Level-2 Emissivity Standa...   \n",
    "ST_TRAD                    Landsat Collection 2 Level-2 Thermal Radiance ...   \n",
    "ST_URAD                    Landsat Collection 2 Level-2 Upwelled Radiance...   \n",
    "MTL.json                   Collection 2 Level-1 Product Metadata File (json)   \n",
    "QA_PIXEL                   Collection 2 Level-1 Pixel Quality Assessment ...   \n",
    "ST_ATRAN                   Landsat Collection 2 Level-2 Atmospheric Trans...   \n",
    "ST_CDIST                   Landsat Collection 2 Level-2 Cloud Distance Ba...   \n",
    "QA_RADSAT                  Collection 2 Level-1 Radiometric Saturation Qu...   \n",
    "thumbnail                                                                NaN   \n",
    "SR_QA_AEROSOL              Collection 2 Level-2 Aerosol Quality Analysis ...   \n",
    "reduced_resolution_browse                                                NaN   \n",
    "\n",
    "                             gsd  \n",
    "ANG                          NaN  \n",
    "SR_B1                       30.0  \n",
    "SR_B2                       30.0  \n",
    "SR_B3                       30.0  \n",
    "SR_B4                       30.0  \n",
    "SR_B5                       30.0  \n",
    "SR_B6                       30.0  \n",
    "SR_B7                       30.0  \n",
    "ST_QA                       30.0  \n",
    "ST_B10                     100.0  \n",
    "MTL.txt                      NaN  \n",
    "MTL.xml                      NaN  \n",
    "ST_DRAD                     30.0  \n",
    "ST_EMIS                     30.0  \n",
    "ST_EMSD                     30.0  \n",
    "ST_TRAD                     30.0  \n",
    "ST_URAD                     30.0  \n",
    "MTL.json                     NaN  \n",
    "QA_PIXEL                    30.0  \n",
    "ST_ATRAN                    30.0  \n",
    "ST_CDIST                    30.0  \n",
    "QA_RADSAT                   30.0  \n",
    "thumbnail                    NaN  \n",
    "SR_QA_AEROSOL               30.0  \n",
    "reduced_resolution_browse    NaN  "
    ]
    },
    "execution_count": 19,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "pd.DataFrame.from_dict(landsat.extra_fields[\"item_assets\"], orient=\"index\")[\n",
    "    [\"title\", \"description\", \"gsd\"]\n",
    "]"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "d951c06c-8d3a-47e7-8067-47fe4e9d4ccf",
    "metadata": {},
    "source": [
    "Some collections, like [Daymet](https://planetarycomputer.microsoft.com/dataset/daymet-daily-na) include collection-level assets. You can use the `.assets` property to access those assets."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 20,
    "id": "c2ffb4ee-2714-4bf0-8445-5d90fcc2520c",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/plain": [
    "<CollectionClient id=daymet-daily-na>"
    ]
    },
    "execution_count": 20,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "collection = catalog.get_collection(\"daymet-daily-na\")\n",
    "collection"
    ]
    },
    {
    "cell_type": "markdown",
    "id": "520e7e3f-b189-4ce3-b5f1-11211e474d1b",
    "metadata": {},
    "source": [
    "Just like assets on items, these assets include links to data in Azure Blob Storage."
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 21,
    "id": "08b95491-3994-4cc5-8b24-ba113874835f",
    "metadata": {},
    "outputs": [
    {
    "data": {
    "text/plain": [
    "<Asset href=https://daymeteuwest.blob.core.windows.net/daymet-zarr/daily/na.zarr>"
    ]
    },
    "execution_count": 21,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "asset = collection.assets[\"zarr-https\"]\n",
    "asset"
    ]
    },
    {
    "cell_type": "code",
    "execution_count": 22,
    "id": "58b7f436-d739-40d8-93bc-631a2295709a",
    "metadata": {},
    "outputs": [
    {
    "data": {
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    "Dimensions:                  (time: 14965, y: 8075, x: 7814, nv: 2)\n",
    "Coordinates:\n",
    "    lat                      (y, x) float32 dask.array&lt;chunksize=(284, 584), meta=np.ndarray&gt;\n",
    "    lon                      (y, x) float32 dask.array&lt;chunksize=(284, 584), meta=np.ndarray&gt;\n",
    "  * time                     (time) datetime64[ns] 1980-01-01T12:00:00 ... 20...\n",
    "  * x                        (x) float32 -4.56e+06 -4.559e+06 ... 3.253e+06\n",
    "  * y                        (y) float32 4.984e+06 4.983e+06 ... -3.09e+06\n",
    "Dimensions without coordinates: nv\n",
    "Data variables:\n",
    "    dayl                     (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    lambert_conformal_conic  int16 ...\n",
    "    prcp                     (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    srad                     (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    swe                      (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    time_bnds                (time, nv) datetime64[ns] dask.array&lt;chunksize=(365, 2), meta=np.ndarray&gt;\n",
    "    tmax                     (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    tmin                     (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    vp                       (time, y, x) float32 dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;\n",
    "    yearday                  (time) int16 dask.array&lt;chunksize=(365,), meta=np.ndarray&gt;\n",
    "Attributes:\n",
    "    Conventions:       CF-1.6\n",
    "    Version_data:      Daymet Data Version 4.0\n",
    "    Version_software:  Daymet Software Version 4.0\n",
    "    citation:          Please see http://daymet.ornl.gov/ for current Daymet ...\n",
    "    references:        Please see http://daymet.ornl.gov/ for current informa...\n",
    "    source:            Daymet Software Version 4.0\n",
    "    start_year:        1980</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-07b825c4-d554-4b45-805f-6382e6b20d33' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-07b825c4-d554-4b45-805f-6382e6b20d33' 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>: 14965</li><li><span class='xr-has-index'>y</span>: 8075</li><li><span class='xr-has-index'>x</span>: 7814</li><li><span>nv</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-20fd0410-313e-4e2d-8ef2-5318e1d81dd3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-20fd0410-313e-4e2d-8ef2-5318e1d81dd3' class='xr-section-summary' >Coordinates: <span>(5)</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'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(284, 584), meta=np.ndarray&gt;</div><input id='attrs-7a144681-315d-4851-b030-5de6652a544b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a144681-315d-4851-b030-5de6652a544b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2df6773-d271-4eac-b53f-2a3c93167dd5' class='xr-var-data-in' type='checkbox'><label for='data-f2df6773-d271-4eac-b53f-2a3c93167dd5' 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",
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    "                </thead>\n",
    "                <tbody>\n",
    "                    \n",
    "                    <tr>\n",
    "                        <th> Bytes </th>\n",
    "                        <td> 240.70 MiB </td>\n",
    "                        <td> 647.88 kiB </td>\n",
    "                    </tr>\n",
    "                    \n",
    "                    <tr>\n",
    "                        <th> Shape </th>\n",
    "                        <td> (8075, 7814) </td>\n",
    "                        <td> (284, 584) </td>\n",
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    "                    <tr>\n",
    "                        <th> Count </th>\n",
    "                        <td> 407 Tasks </td>\n",
    "                        <td> 406 Chunks </td>\n",
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    "                    <tr>\n",
    "                    <th> Type </th>\n",
    "                    <td> float32 </td>\n",
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    "</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'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(284, 584), meta=np.ndarray&gt;</div><input id='attrs-7a193b99-b4d3-4393-bf9a-92422daba328' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a193b99-b4d3-4393-bf9a-92422daba328' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f77d7c3-c64d-42d3-b09f-928758da7184' class='xr-var-data-in' type='checkbox'><label for='data-2f77d7c3-c64d-42d3-b09f-928758da7184' 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",
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    "                        <td> (284, 584) </td>\n",
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    "</table></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'>1980-01-01T12:00:00 ... 2020-12-...</div><input id='attrs-a419e0cd-5efc-4c01-96a2-96e309cbd37e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a419e0cd-5efc-4c01-96a2-96e309cbd37e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bad30ca-bedc-4cf7-b1e5-d993b835a427' class='xr-var-data-in' type='checkbox'><label for='data-8bad30ca-bedc-4cf7-b1e5-d993b835a427' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>24-hour day based on local time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T12:00:00.000000000&#x27;, &#x27;1980-01-02T12:00:00.000000000&#x27;,\n",
    "       &#x27;1980-01-03T12:00:00.000000000&#x27;, ..., &#x27;2020-12-28T12:00:00.000000000&#x27;,\n",
    "       &#x27;2020-12-29T12:00:00.000000000&#x27;, &#x27;2020-12-30T12:00:00.000000000&#x27;],\n",
    "      dtype=&#x27;datetime64[ns]&#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'>float32</div><div class='xr-var-preview xr-preview'>-4.56e+06 -4.559e+06 ... 3.253e+06</div><input id='attrs-d0dd137a-5ba2-4703-b3fa-a810ffcd75a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0dd137a-5ba2-4703-b3fa-a810ffcd75a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7912f9ae-5d22-42ff-8b1b-fd81958a5150' class='xr-var-data-in' type='checkbox'><label for='data-7912f9ae-5d22-42ff-8b1b-fd81958a5150' 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>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-4560250., -4559250., -4558250., ...,  3250750.,  3251750.,  3252750.],\n",
    "      dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>4.984e+06 4.983e+06 ... -3.09e+06</div><input id='attrs-5a511e64-2ee0-4ba3-a3ac-fb5e2770a24a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a511e64-2ee0-4ba3-a3ac-fb5e2770a24a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffb40ac1-9ace-499a-bf87-b99b1bbf480a' class='xr-var-data-in' type='checkbox'><label for='data-ffb40ac1-9ace-499a-bf87-b99b1bbf480a' 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>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 4984000.,  4983000.,  4982000., ..., -3088000., -3089000., -3090000.],\n",
    "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ee857937-6790-424f-881a-b8f920784ee6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ee857937-6790-424f-881a-b8f920784ee6' class='xr-section-summary' >Data variables: <span>(10)</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>dayl</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;</div><input id='attrs-28141e79-fdc5-4e78-a8e4-295a43e1c49d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28141e79-fdc5-4e78-a8e4-295a43e1c49d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca574813-9045-42bc-b302-9fed153504d7' class='xr-var-data-in' type='checkbox'><label for='data-ca574813-9045-42bc-b302-9fed153504d7' 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>cell_methods :</span></dt><dd>area: mean</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>daylength</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><table>\n",
    "    <tr>\n",
    "        <td>\n",
    "            <table>\n",
    "                <thead>\n",
    "                    <tr>\n",
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    "                <tbody>\n",
    "                    \n",
    "                    <tr>\n",
    "                        <th> Bytes </th>\n",
    "                        <td> 3.44 TiB </td>\n",
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    "                    <tr>\n",
    "                        <th> Shape </th>\n",
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    "                        <td> (365, 284, 584) </td>\n",
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    "                    <tr>\n",
    "                        <th> Count </th>\n",
    "                        <td> 16647 Tasks </td>\n",
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    "                    <tr>\n",
    "                    <th> Type </th>\n",
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    "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lambert_conformal_conic</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b166cf18-26e1-4910-87b1-0080cf8f1969' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b166cf18-26e1-4910-87b1-0080cf8f1969' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cb354bc-25a9-412a-8e92-c57d9fe09999' class='xr-var-data-in' type='checkbox'><label for='data-8cb354bc-25a9-412a-8e92-c57d9fe09999' 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>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>42.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-100.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>standard_parallel :</span></dt><dd>[25.0, 60.0]</dd></dl></div><div class='xr-var-data'><pre>array(-32767, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcp</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;</div><input id='attrs-04d357b4-c597-41d1-9d1d-2ad18f4bffa6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04d357b4-c597-41d1-9d1d-2ad18f4bffa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4cf3b61-9a4b-4799-892c-723751111ca4' class='xr-var-data-in' type='checkbox'><label for='data-e4cf3b61-9a4b-4799-892c-723751111ca4' 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>cell_methods :</span></dt><dd>area: mean time: sum</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>daily total precipitation</dd><dt><span>units :</span></dt><dd>mm/day</dd></dl></div><div class='xr-var-data'><table>\n",
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    "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>srad</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(365, 284, 584), meta=np.ndarray&gt;</div><input id='attrs-8c4d0577-cafb-4284-9392-4d36431dbde6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c4d0577-cafb-4284-9392-4d36431dbde6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9d08a82-0231-4629-8415-368b99104459' class='xr-var-data-in' type='checkbox'><label for='data-e9d08a82-0231-4629-8415-368b99104459' 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>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>grid_mapping :</span></dt><dd>lambert_conformal_conic</dd><dt><span>long_name :</span></dt><dd>daylight average incident shortwave radiation</dd><dt><span>units :</span></dt><dd>W/m2</dd></dl></div><div class='xr-var-data'><table>\n",
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    "                    <tr>\n",
    "                    <th> Type </th>\n",
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    "                    <tr>\n",
    "                        <th> Bytes </th>\n",
    "                        <td> 3.44 TiB </td>\n",
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    "        </td>\n",
    "    </tr>\n",
    "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>yearday</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(365,), meta=np.ndarray&gt;</div><input id='attrs-93748e9f-d358-459f-9ff0-fd3f5a85d2c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93748e9f-d358-459f-9ff0-fd3f5a85d2c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a6556f7-a4d5-48d5-9407-90023fa65eb3' class='xr-var-data-in' type='checkbox'><label for='data-3a6556f7-a4d5-48d5-9407-90023fa65eb3' 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>day of year (DOY) starting with day 1 on Januaray 1st</dd></dl></div><div class='xr-var-data'><table>\n",
    "    <tr>\n",
    "        <td>\n",
    "            <table>\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> 29.23 kiB </td>\n",
    "                        <td> 730 B </td>\n",
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    "                    \n",
    "                    <tr>\n",
    "                        <th> Shape </th>\n",
    "                        <td> (14965,) </td>\n",
    "                        <td> (365,) </td>\n",
    "                    </tr>\n",
    "                    <tr>\n",
    "                        <th> Count </th>\n",
    "                        <td> 42 Tasks </td>\n",
    "                        <td> 41 Chunks </td>\n",
    "                    </tr>\n",
    "                    <tr>\n",
    "                    <th> Type </th>\n",
    "                    <td> int16 </td>\n",
    "                    <td> numpy.ndarray </td>\n",
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    "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba5808e8-c515-4391-a633-25a9f9a5ad50' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ba5808e8-c515-4391-a633-25a9f9a5ad50' class='xr-section-summary' >Attributes: <span>(7)</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>Version_data :</span></dt><dd>Daymet Data Version 4.0</dd><dt><span>Version_software :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>citation :</span></dt><dd>Please see http://daymet.ornl.gov/ for current Daymet data citation information</dd><dt><span>references :</span></dt><dd>Please see http://daymet.ornl.gov/ for current information on Daymet references</dd><dt><span>source :</span></dt><dd>Daymet Software Version 4.0</dd><dt><span>start_year :</span></dt><dd>1980</dd></dl></div></li></ul></div></div>"
    ],
    "text/plain": [
    "<xarray.Dataset>\n",
    "Dimensions:                  (time: 14965, y: 8075, x: 7814, nv: 2)\n",
    "Coordinates:\n",
    "    lat                      (y, x) float32 dask.array<chunksize=(284, 584), meta=np.ndarray>\n",
    "    lon                      (y, x) float32 dask.array<chunksize=(284, 584), meta=np.ndarray>\n",
    "  * time                     (time) datetime64[ns] 1980-01-01T12:00:00 ... 20...\n",
    "  * x                        (x) float32 -4.56e+06 -4.559e+06 ... 3.253e+06\n",
    "  * y                        (y) float32 4.984e+06 4.983e+06 ... -3.09e+06\n",
    "Dimensions without coordinates: nv\n",
    "Data variables:\n",
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    "    lambert_conformal_conic  int16 ...\n",
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    "    yearday                  (time) int16 dask.array<chunksize=(365,), meta=np.ndarray>\n",
    "Attributes:\n",
    "    Conventions:       CF-1.6\n",
    "    Version_data:      Daymet Data Version 4.0\n",
    "    Version_software:  Daymet Software Version 4.0\n",
    "    citation:          Please see http://daymet.ornl.gov/ for current Daymet ...\n",
    "    references:        Please see http://daymet.ornl.gov/ for current informa...\n",
    "    source:            Daymet Software Version 4.0\n",
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    ]
    },
    "execution_count": 22,
    "metadata": {},
    "output_type": "execute_result"
    }
    ],
    "source": [
    "import fsspec\n",
    "import xarray as xr\n",
    "\n",
    "store = fsspec.get_mapper(asset.href)\n",
    "ds = xr.open_zarr(store, **asset.extra_fields[\"xarray:open_kwargs\"])\n",
    "ds"
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