Image/cumulative_cost_mapping.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/Image/cumulative_cost_mapping.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/Image/cumulative_cost_mapping.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/Image/cumulative_cost_mapping.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
        "</table>"
      ]
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    {
      "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",
        "# A rectangle representing Bangui, Central African Republic.\n",
        "geometry = ee.Geometry.Rectangle([18.5229, 4.3491, 18.5833, 4.4066])\n",
        "\n",
        "# Create a source image where the geometry is 1, everything else is 0.\n",
        "sources = ee.Image().toByte().paint(geometry, 1)\n",
        "\n",
        "# Mask the sources image with itself.\n",
        "sources = sources.updateMask(sources)\n",
        "\n",
        "# The cost data is generated from classes in ESA/GLOBCOVER.\n",
        "cover = ee.Image('ESA/GLOBCOVER_L4_200901_200912_V2_3').select(0)\n",
        "\n",
        "# Classes 60, 80, 110, 140 have cost 1.\n",
        "# Classes 40, 90, 120, 130, 170 have cost 2.\n",
        "# Classes 50, 70, 150, 160 have cost 3.\n",
        "cost = \\\n",
        "  cover.eq(60).Or(cover.eq(80)).Or(cover.eq(110)).Or(cover.eq(140)) \\\n",
        "      .multiply(1).add(\n",
        "  cover.eq(40).Or(cover.eq(90)).Or(cover.eq(120)).Or(cover.eq(130)) \\\n",
        "    .Or(cover.eq(170)) \\\n",
        "      .multiply(2).add(\n",
        "  cover.eq(50).Or(cover.eq(70)).Or(cover.eq(150)).Or(cover.eq(160)) \\\n",
        "      .multiply(3)))\n",
        "\n",
        "# Compute the cumulative cost to traverse the lAnd cover.\n",
        "cumulativeCost = cost.cumulativeCost(**{\n",
        "  'source': sources,\n",
        "  'maxDistance': 80 * 1000 # 80 kilometers\n",
        "})\n",
        "\n",
        "# Display the results\n",
        "Map.setCenter(18.71, 4.2, 9)\n",
        "Map.addLayer(cover, {}, 'Globcover')\n",
        "Map.addLayer(cumulativeCost, {'min': 0, 'max': 5e4}, 'accumulated cost')\n",
        "Map.addLayer(geometry, {'color': 'FF0000'}, 'source geometry')\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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