![]() name: North America - onshore and offshore: Canada - Alberta British Columbia Manitoba New Brunswick Newfoundland and Labrador Northwest Territories Nova Scotia Nunavut Ontario Prince Edward Island Quebec Saskatchewan Yukon. Notice that you are loading the plotting_extent function from the plot module of the rasterio package. To begin, load all of the required libraries. You can use the plotting_extent function from rasterio in combination with the data you opened in rioxarray to create the spatial plotting extent for a raster layer, using the DataArray and the other metadata stored in the DataArray object. In order to plot the raster and vector data together in the same plot, you need to identify the spatial extent of the raster data file so that matplotlib can correctly place the raster data in geographic space. If you want to overlay a spatial vector layer on top of that raster, the data will not line up correctly. Due to this, the plot will begin at the x,y location: 0,0. This means the corner location of the raster is unknown since the numpy array doesn’t contain any of the spatial information. When you plot the DataArray with earthpy, you extract a numpy array from it with the. If you are reading in your raster data using rioxarray, your data will be returned as a DataArray containing the raster data values and all spatial information associated with the values. ![]() You often want to create a map that includes a raster layer (for example a satelite image) with vector data such as political boundaries or study area boundaries overlayed on top of that raster layer. Use a plotting_extent object to plot spatial vector and raster data together using matplotlib.Create a custom plotting_extent object using rasterio.
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