AssetManagement/export_ImageCollection.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/AssetManagement/export_ImageCollection.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/AssetManagement/export_ImageCollection.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/AssetManagement/export_ImageCollection.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",
        "# USDA NAIP ImageCollection\n",
        "collection = ee.ImageCollection('USDA/NAIP/DOQQ')\n",
        "\n",
        "# create an roi\n",
        "polys = ee.Geometry.Polygon(\n",
        "        [[[-99.29615020751953, 46.725459351792374],\n",
        "          [-99.2116928100586, 46.72404725733022],\n",
        "          [-99.21443939208984, 46.772037733479884],\n",
        "          [-99.30267333984375, 46.77321343419932]]])\n",
        "\n",
        "# create a FeatureCollection based on the roi and center the map\n",
        "centroid = polys.centroid()\n",
        "lng, lat = centroid.getInfo()['coordinates']\n",
        "print(\"lng = {}, lat = {}\".format(lng, lat))\n",
        "Map.setCenter(lng, lat, 12)\n",
        "fc = ee.FeatureCollection(polys)\n",
        "\n",
        "# filter the ImageCollection using the roi\n",
        "naip = collection.filterBounds(polys)\n",
        "naip_2015 = naip.filterDate('2015-01-01', '2015-12-31')\n",
        "mosaic = naip_2015.mosaic()\n",
        "\n",
        "# print out the number of images in the ImageCollection\n",
        "count = naip_2015.size().getInfo()\n",
        "print(\"Count: \", count)\n",
        "\n",
        "# add the ImageCollection and the roi to the map\n",
        "vis = {'bands': ['N', 'R', 'G']}\n",
        "Map.addLayer(mosaic,vis)\n",
        "Map.addLayer(fc)\n",
        "\n",
        "# export the ImageCollection to Google Drive\n",
        "downConfig = {'scale': 30, \"maxPixels\": 1.0E13, 'driveFolder': 'image'}  # scale means resolution.\n",
        "img_lst = naip_2015.toList(100)\n",
        "\n",
        "for i in range(0, count):\n",
        "    image = ee.Image(img_lst.get(i))\n",
        "    name = image.get('system:index').getInfo()\n",
        "    # print(name)\n",
        "    task = ee.batch.Export.image(image, name, downConfig)\n",
        "    task.start()\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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