Finally, the resulting FC will be transformed into a GeoDataFrame and save as a shapefile into our working directory. After that, we will create 2000 random points that will be used to sample the Image using the mean. The resulting image will be clipped to the previously created polygon.
Next, we will select the required data and calculate the mode. Second, we will create a rectangle that will be used to clip the data. To obtain 100-Hour Fuel Moisture, Wind Direction, and Wind Velocity data from GEE we need first to call the GRIDMET ImageCollection and filter by date. # get World Data Protected Areas (WDPA) FeatureCollection pa = ee.FeatureCollection("WCMC/WDPA/current/polygons") # Yosemite National Park polygon filter = ee.Filter.inList('NAME', ) yosemite = pa.filter(filter) # transform Yosemite fc into gdf yosGDF = eeconvert.fcToGdf(yosemite) # convert gdf into shp yosGDF.to_file("gisdata/yosemite/shp/yosemite.shp") We will convert the extracted FC into a GeoDataFrame (GDF) and save it as a shapefile into our working directory. We will call the WDPA FeatureCollection (FC) and extract the Yosemite National Park polygon.
You need to install the following packages that are not contained in Anaconda: Geopandas, GEE Python API, eeconvert, geemap.
Our Python environment is based on an Anaconda installation on Ubuntu 20.04. You also need to install the latest version of GRASS GIS and have an active GEE account. This tutorial assumes you are working in a Jupyter Notebook and a Python environment with all required packages.