geemap-datapane

geemap_test.ipynb

{
  "cells": [
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import folium\nimport datapane as dp \nimport geemap.eefolium as geemap\nimport ee\nimport os\n\n# # ee_token = os.environ['EARTHENGINE_TOKEN']\n# secret = dp.Variable.get(name='EARTHENGINE_TOKEN')\n# # secret = dp.Variable.get(name='EARTHENGINE_TOKEN', owner='giswqs')\n# ee_token = secret.value\n\n# credential = '{\"refresh_token\":\"%s\"}' % ee_token\n# credential_file_path = os.path.expanduser(\"~/.config/earthengine/\")\n# os.makedirs(credential_file_path, exist_ok=True)\n# with open(credential_file_path + 'credentials', 'w') as file:\n#     file.write(credential)\n\n# m = folium.Map(location=[45.5236, -122.6750])\nee.Initialize()\nMap = geemap.Map(center=[40,-100], zoom=4)\nMap.add_basemap('ROADMAP') # Add Google Map\n\n# Add Earth Engine dataset\nimage = ee.Image('USGS/SRTMGL1_003')\n\n# Set visualization parameters.\nvis_params = {\n  'min': 0,\n  'max': 4000,\n  'palette': ['006633', 'E5FFCC', '662A00', 'D8D8D8', 'F5F5F5']}\n\n# Print the elevation of Mount Everest.\nxy = ee.Geometry.Point([86.9250, 27.9881])\nelev = image.sample(xy, 30).first().get('elevation').getInfo()\nprint('Mount Everest elevation (m):', elev)\n\n# Add Earth Engine layers to Map\nMap.addLayer(image, vis_params, 'DEM')\nMap.addLayer(xy, {'color': 'red'}, 'Mount Everest')\n\n# Center the map based on an Earth Engine object or coordinates (longitude, latitude)\n# Map.centerObject(xy, 4)\nMap.setCenter(86.9250, 27.9881, 4)\n\n# Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\nMap.setControlVisibility()\n\n# dp.Report(dp.Plot(Map)).publish(name='geemap_folium_map')\ndp.Report(dp.Plot(Map)).preview(width='100%')",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Mount Everest elevation (m): 8729\n",
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "execution_count": 1,
          "data": {
            "text/plain": "<IPython.lib.display.IFrame at 0x7f8f5995be50>",
            "text/html": "\n        <iframe\n            width=\"100%\"\n            height=\"500\"\n            src=\"dp-tmp-de23rmqj/dp-tmp-k7yf26y9.html\"\n            frameborder=\"0\"\n            allowfullscreen\n        ></iframe>\n        "
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "toc": {
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": true,
      "base_numbering": 1,
      "title_cell": "Table of Contents",
      "title_sidebar": "Table of Contents",
      "toc_cell": false,
      "toc_position": {},
      "toc_section_display": true,
      "toc_window_display": true
    },
    "language_info": {
      "name": "python",
      "version": "3.8.2",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    },
    "gist": {
      "id": "",
      "data": {
        "description": "geemap-datapane",
        "public": true
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}