Reducer/convert_raster_to_vector.ipynb

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        "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
        "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/earthengine-py-notebooks/tree/master/Reducer/convert_raster_to_vector.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Reducer/convert_raster_to_vector.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Reducer/convert_raster_to_vector.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Install Earth Engine API and geemap\n",
        "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://geemap.org). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n",
        "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Installs geemap package\n",
        "import subprocess\n",
        "\n",
        "try:\n",
        "    import geemap\n",
        "except ImportError:\n",
        "    print('Installing geemap ...')\n",
        "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "import ee\n",
        "import geemap"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Create an interactive map \n",
        "The default basemap is `Google Maps`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/basemaps.py) can be added using the `Map.add_basemap()` function. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map = geemap.Map(center=[40,-100], zoom=4)\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Add Earth Engine Python script "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Add Earth Engine dataset\n",
        "# Load a Japan boundary from the Large Scale International Boundary dataset.\n",
        "japan = ee.FeatureCollection('USDOS/LSIB_SIMPLE/2017') \\\n",
        "  .filter(ee.Filter.eq('country_na', 'Japan'))\n",
        "\n",
        "# Load a 2012 nightlights image, clipped to the Japan border.\n",
        "nl2012 = ee.Image('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F182012') \\\n",
        "  .select('stable_lights') \\\n",
        "  .clipToCollection(japan)\n",
        "\n",
        "# Define arbitrary thresholds on the 6-bit nightlights image.\n",
        "zones = nl2012.gt(30).add(nl2012.gt(55)).add(nl2012.gt(62))\n",
        "zones = zones.updateMask(zones.neq(0))\n",
        "\n",
        "# Convert the zones of the thresholded nightlights to vectors.\n",
        "vectors = zones.addBands(nl2012).reduceToVectors(**{\n",
        "  'geometry': japan,\n",
        "  'crs': nl2012.projection(),\n",
        "  'scale': 1000,\n",
        "  'geometryType': 'polygon',\n",
        "  'eightConnected': False,\n",
        "  'labelProperty': 'zone',\n",
        "  'reducer': ee.Reducer.mean()\n",
        "})\n",
        "\n",
        "# Display the thresholds.\n",
        "Map.setCenter(139.6225, 35.712, 9)\n",
        "Map.addLayer(zones, {'min': 1, 'max': 3, 'palette': ['0000FF', '00FF00', 'FF0000']}, 'raster')\n",
        "\n",
        "# Make a display image for the vectors, add it to the map.\n",
        "display = ee.Image(0).updateMask(0).paint(vectors, '000000', 3)\n",
        "Map.addLayer(display, {'palette': '000000'}, 'vectors')\n",
        "\n"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Display Earth Engine data layers "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    }
  ],
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