crib-hackathon/Challenge2_GE.ipynb

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    "# Challenge II – Water body mapping using the Google Earth Engine \n",
    "\n",
    "The Google Earth Engine is a popular tool in the geospatial community. It offers an extensive catalog of (pre-processed) satellite and geospatial data, in combination with processing capabilities which can be called using JavaScript or Python. It is also possible to interact with the Google Earth Engine via a Jupyter notebook or on the CRIB platform. \n",
    "\n",
    "![image.png](attachment:455b1e1b-ef21-4d7f-9255-b78c3154cd48.png)\n",
    "## Objectives \n",
    "\n",
    "1. Explore interacting with the Google Earth Engine on the CRIB platform.  \n",
    "\n",
    "2. Classify water/non-water in a region of interest. Two simple methods are (i) the Normalized Difference Water Index (NDWI) or \n",
    "    (ii) Synthetic Aperture Radar backscatter below a certain threshold. For (i) Landsat or Sentinel-2 imagery could be used and for (ii) Sentinel-1 imagery could be used, which are all available on the Google Earth Engine.  \n",
    "\n",
    "3. Present your results on a Jupyter notebook. \n",
    "\n",
    " \n",
    "\n",
    "Applying for a Google Earth Engine account may take a few days, so if you want to do this challenge it is important that you have timely applied for the account. \n",
    "\n",
    " \n",
    "\n",
    "## Resources \n",
    "\n",
    "https://developers.google.com/earth-engine/guides/python_install \n",
    "\n",
    "ee is the Python API package, allowing to interact with the Google Earth Engine. This package has been made available on the CRIB platform.  \n",
    "\n",
    "\n",
    "\n",
    "https://geemap.org/ \n",
    "\n",
    "Geemap is a Python package which adds functionality to use, process and visualize Google Earth Engine datasets. This package has been made available on the CRIB platform. \n",
    "\n",
    " \n",
    "\n",
    "https://tutorials.geemap.org/ \n",
    "\n",
    "Tutorial that explains the basic functionalities of ee and geemap. Contains a number of examples, which can directly be applied. \n",
    "\n",
    " \n",
    "\n",
    "https://github.com/giswqs/earthengine-py-notebooks \n",
    "\n",
    "A large number of complete examples. See, for example, ‘ndvi_symbology’ (NWDI is similar to NDVI) and ‘conditional_operations’ (identify pixels with a backscatter value lower than a defined threshold). "
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