datasets/chesapeake/chesapeake-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d2583da9-3f1e-40e6-b81d-700f26e89daa",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Accessing Chesapeake Land Use data with the Planetary Computer STAC API\n",
    "\n",
    "The [Chesapeake Land Use](https://www.chesapeakeconservancy.org/conservation-innovation-center/high-resolution-data/land-use-data-project/) dataset is high-resolution 1-meter Land Use data product in raster format for the entire Chesapeake Bay watershed. The dataset was created by modifying the 2013-2014 high-resolution land cover dataset using 13 ancillary datasets including data on zoning, land use, parcel boundaries, landfills, floodplains, and wetlands. The product area encompasses over 250,000 square kilometers in New York, Pennsylvania, Maryland, Delaware, West Virginia, Virginia, and the District of Columbia. The dataset was created by the Chesapeake Conservancy Conservation Innovation Center for the Chesapeake Bay Program, which is a regional partnership of EPA, other federal, state, and local agencies and governments, nonprofits, and academic institutions that leads and directs Chesapeake Bay restoration efforts.\n",
    "\n",
    "In this notebook, we'll demonstrate how to access and work with this data through the Planetary Computer. Documentation for this dataset is available at the [Planetary Computer Data Catalog](https://planetarycomputer.microsoft.com/dataset/chesapeake-lu).\n",
    "\n",
    "### Environment setup\n",
    "\n",
    "This notebook works with or without an API key, but you will be given more permissive access to the data with an API key.\n",
    "\n",
    "* The [Planetary Computer Hub](https://planetarycomputer.microsoft.com/compute) is pre-configured to use your API key.\n",
    "* To use your API key locally, set the environment variable `PC_SDK_SUBSCRIPTION_KEY` or use `planetary_computer.settings.set_subscription_key(<YOUR API Key>)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f3f030fa-8639-4b4e-b0a1-f3226375c28e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pystac_client\n",
    "from pystac.extensions.item_assets import ItemAssetsExtension\n",
    "import planetary_computer\n",
    "\n",
    "import matplotlib.colors\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import requests\n",
    "import rioxarray\n",
    "import rich.table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "527d242e-32b4-49fb-a513-a74ee38495da",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Query for data of interest\n",
    "\n",
    "We'll query for 2013 Chesapeake Land Use data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7e037147-5996-4532-a02c-5ce3d15b9a68",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fetching 2013\n",
      "Returned 166 Items\n"
     ]
    }
   ],
   "source": [
    "catalog = pystac_client.Client.open(\n",
    "    \"https://pct-apis-staging.westeurope.cloudapp.azure.com/stac/\"\n",
    ")\n",
    "\n",
    "latitude = 39.29\n",
    "longitude = -76.61\n",
    "datetimes = [\"2013\"]\n",
    "\n",
    "buffer = 0.6\n",
    "bbox = [longitude - buffer, latitude - buffer, longitude + buffer, latitude + buffer]\n",
    "items = dict()\n",
    "\n",
    "for datetime in datetimes:\n",
    "    print(f\"Fetching {datetime}\")\n",
    "    search = catalog.search(collections=[\"chesapeake-lu\"], bbox=bbox, datetime=datetime)\n",
    "\n",
    "items = list(search.get_items())\n",
    "print(f\"Returned {len(items)} Items\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49363704-3dd9-4f50-a8d2-b4b4c61f8360",
   "metadata": {},
   "source": [
    "Each Item contains a single \"data\" asset with a URL to the location of the Asset data on [Azure Blob Storage](https://azure.microsoft.com/en-us/services/storage/blobs/). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7bd73779-0545-4368-bf96-3d9cce489f97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://landcoverdata.blob.core.windows.net/chesapeake/lu/BayWide_1m_LU_E1700000_N1960000.tif\n"
     ]
    }
   ],
   "source": [
    "asset_href = items[0].assets[\"data\"].href\n",
    "print(asset_href)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6ccf07a-33bd-4be7-85c1-4471a17ae176",
   "metadata": {},
   "source": [
    "### Available STAC assets and metadata\n",
    "\n",
    "Let's check the available assets and metadata for the Chesapeake Land Use item. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a3f2152a-6925-4a01-b24f-485cca0b9f55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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\"> Title                           </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│ data             │ Land Use Classes                │\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[1mTitle                          \u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│ data             │ Land Use Classes                │\n",
       "│ tilejson         │ TileJSON with default rendering │\n",
       "│ rendered_preview │ Rendered preview                │\n",
       "└──────────────────┴─────────────────────────────────┘\n"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = rich.table.Table(\"Asset key\", \"Title\")\n",
    "for k, asset in items[0].assets.items():\n",
    "    t.add_row(k, asset.title)\n",
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "485ef558-d85e-41b4-898b-d799f205d45f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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\"> Key            </span>┃<span style=\"font-weight: bold\"> Value                                                                                          </span>┃\n",
       "┡━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│ created        │ 2022-06-01T20:15:13.334677Z                                                                    │\n",
       "│ datetime       │ None                                                                                           │\n",
       "│ end_datetime   │ 2014-12-31T23:59:59Z                                                                           │\n",
       "│ proj:epsg      │ None                                                                                           │\n",
       "│ proj:shape     │ [10000, 10000]                                                                                 │\n",
       "│ proj:transform │ [1.0, 0.0, 1699999.1624823206, 0.0, -1.0, 1970000.8902923968]                                  │\n",
       "│ proj:wkt2      │ PROJCS[\"USA_Contiguous_Albers_Equal_Area_Conic_USGS_version\",GEOGCS[\"NAD83\",DATUM[\"North_Amer… │\n",
       "│                │ 1980\",6378137,298.257222101004,AUTHORITY[\"EPSG\",\"7019\"]],AUTHORITY[\"EPSG\",\"6269\"]],PRIMEM[\"Gr… │\n",
       "│ start_datetime │ 2013-01-01T00:00:00Z                                                                           │\n",
       "└────────────────┴────────────────────────────────────────────────────────────────────────────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mKey           \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mValue                                                                                         \u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│ created        │ 2022-06-01T20:15:13.334677Z                                                                    │\n",
       "│ datetime       │ None                                                                                           │\n",
       "│ end_datetime   │ 2014-12-31T23:59:59Z                                                                           │\n",
       "│ proj:epsg      │ None                                                                                           │\n",
       "│ proj:shape     │ [10000, 10000]                                                                                 │\n",
       "│ proj:transform │ [1.0, 0.0, 1699999.1624823206, 0.0, -1.0, 1970000.8902923968]                                  │\n",
       "│ proj:wkt2      │ PROJCS[\"USA_Contiguous_Albers_Equal_Area_Conic_USGS_version\",GEOGCS[\"NAD83\",DATUM[\"North_Amer… │\n",
       "│                │ 1980\",6378137,298.257222101004,AUTHORITY[\"EPSG\",\"7019\"]],AUTHORITY[\"EPSG\",\"6269\"]],PRIMEM[\"Gr… │\n",
       "│ start_datetime │ 2013-01-01T00:00:00Z                                                                           │\n",
       "└────────────────┴────────────────────────────────────────────────────────────────────────────────────────────────┘\n"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = rich.table.Table(\"Key\", \"Value\")\n",
    "for k, v in sorted(items[0].properties.items()):\n",
    "    t.add_row(k, str(v))\n",
    "\n",
    "t"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f76a3b43-7827-4e8d-9305-6af33794bbce",
   "metadata": {},
   "source": [
    "### Displaying the data\n",
    "\n",
    "This dataset includes a preferred colormap mapping raster values to colors. The Collection's `item_assets` field includes an overview of the class descriptions and values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cd296765-a455-4a92-bd1f-4e29da0344ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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\"> Description                          </span>┃<span style=\"font-weight: bold\"> Value </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n",
       "│ Impervious Roads                     │ 1     │\n",
       "│ Impervious Non-Roads                 │ 2     │\n",
       "│ Tree Canopy over Impervious Surfaces │ 3     │\n",
       "│ Water                                │ 4     │\n",
       "│ Tidal Wetlands                       │ 5     │\n",
       "│ Floodplain Wetlands                  │ 6     │\n",
       "│ Other Wetlands                       │ 7     │\n",
       "│ Forest                               │ 8     │\n",
       "│ Tree Canopy over Turf Grass          │ 9     │\n",
       "│ Mixed Open                           │ 10    │\n",
       "│ Fractional Turf (small)              │ 11    │\n",
       "│ Fractional Turf (medium)             │ 12    │\n",
       "│ Fractional Turf (large)              │ 13    │\n",
       "│ Fractional Impervious                │ 14    │\n",
       "│ Turf Grass                           │ 15    │\n",
       "│ Cropland                             │ 16    │\n",
       "│ Pasture/Hay                          │ 17    │\n",
       "└──────────────────────────────────────┴───────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mDescription                         \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mValue\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n",
       "│ Impervious Roads                     │ 1     │\n",
       "│ Impervious Non-Roads                 │ 2     │\n",
       "│ Tree Canopy over Impervious Surfaces │ 3     │\n",
       "│ Water                                │ 4     │\n",
       "│ Tidal Wetlands                       │ 5     │\n",
       "│ Floodplain Wetlands                  │ 6     │\n",
       "│ Other Wetlands                       │ 7     │\n",
       "│ Forest                               │ 8     │\n",
       "│ Tree Canopy over Turf Grass          │ 9     │\n",
       "│ Mixed Open                           │ 10    │\n",
       "│ Fractional Turf (small)              │ 11    │\n",
       "│ Fractional Turf (medium)             │ 12    │\n",
       "│ Fractional Turf (large)              │ 13    │\n",
       "│ Fractional Impervious                │ 14    │\n",
       "│ Turf Grass                           │ 15    │\n",
       "│ Cropland                             │ 16    │\n",
       "│ Pasture/Hay                          │ 17    │\n",
       "└──────────────────────────────────────┴───────┘\n"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Classifications\n",
    "collection = catalog.get_collection(\"chesapeake-lu\")\n",
    "ia = ItemAssetsExtension.ext(collection)\n",
    "x = ia.item_assets[\"data\"]\n",
    "\n",
    "class_names = {\n",
    "    x[\"description\"]: x[\"value\"] for x in x.properties[\"classification:classes\"]\n",
    "}\n",
    "class_values = {v: k for k, v in class_names.items()}\n",
    "\n",
    "t = rich.table.Table(\"Description\", \"Value\")\n",
    "for k, v in class_names.items():\n",
    "    t.add_row(k, str(v))\n",
    "t"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e8867d7-e6a2-447a-970f-b1a682239655",
   "metadata": {},
   "source": [
    "And the Planetary Computer's [Data API](https://planetarycomputer.microsoft.com/api/data/v1/docs) includes the colormap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "55f58de8-36e4-4db8-98e8-d69f3a2de749",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0': [0, 0, 0, 0],\n",
       " '1': [0, 0, 0, 255],\n",
       " '2': [115, 0, 0, 255],\n",
       " '3': [85, 255, 0, 255],\n",
       " '4': [0, 112, 255, 255],\n",
       " '5': [0, 255, 197, 255],\n",
       " '6': [0, 230, 169, 255],\n",
       " '7': [0, 230, 169, 255],\n",
       " '8': [38, 115, 0, 255],\n",
       " '9': [170, 255, 0, 255],\n",
       " '10': [168, 112, 0, 255],\n",
       " '11': [255, 190, 232, 255],\n",
       " '12': [255, 190, 232, 255],\n",
       " '13': [255, 190, 232, 255],\n",
       " '14': [197, 0, 255, 255],\n",
       " '15': [255, 255, 115, 255],\n",
       " '16': [230, 152, 0, 255],\n",
       " '17': [230, 152, 0, 255],\n",
       " '255': [0, 0, 0, 0]}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classmap = requests.get(\n",
    "    \"https://pct-apis-staging.westeurope.cloudapp.azure.com/data/legend/classmap/chesapeake-lu\"  # noqa: E501\n",
    ").json()\n",
    "classmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cae2e2d4-9c5b-46e7-8f18-7bd78fee055b",
   "metadata": {},
   "source": [
    "We'll convert those values to a [matplotlib Colormap](https://matplotlib.org/stable/api/_as_gen/matplotlib.colors.ListedColormap.html) for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ef1d08dd-0427-4489-a512-7a0d99da5e97",
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = [matplotlib.colors.to_rgba([x / 255 for x in c]) for c in classmap.values()]\n",
    "cmap = matplotlib.colors.ListedColormap(colors, name=\"chesapeak-lu\")\n",
    "ticks = np.arange(cmap.N)\n",
    "labels = [class_values.get(value, \"nodata\") for value in ticks]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4a4cab6-b221-4f5f-9536-dc80d6ce86b2",
   "metadata": {},
   "source": [
    "Finally, we can read the data and plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82426bf9-db88-45f1-963a-e671e6751d56",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = rioxarray.open_rasterio(\n",
    "    planetary_computer.sign(items[0].assets[\"data\"]).href\n",
    ").squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "47c95711-fc9f-4591-bfdd-1b93b6521c89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 12))\n",
    "\n",
    "ds.isel(x=slice(3000), y=slice(3000)).plot(\n",
    "    ax=ax, cmap=cmap, norm=matplotlib.colors.NoNorm()\n",
    ")\n",
    "ax.set_axis_off()\n",
    "ax.set(title=None)\n",
    "\n",
    "colorbar = fig.axes[1]\n",
    "colorbar.set_yticks(ticks, labels=labels);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}