Py-earthpy

Plot and manipulate spatial data in Python

Python is a generic programming language designed to support many different applications. Because of this, many commonly performed spatial tasks for science including plotting and working with spatial data take many steps of code. EarthPy builds upon the functionality developed for raster data rasterio and vector data geopandas in Python and simplifies the code needed to

• Stack and crop raster bands from data such as Landsat into an easy to use numpy array;
• Work with masks to set bad pixels such a those covered by clouds and cloud-shadows to NA mask_pixels;
• Plot rgb color, color infrared and other 3 band combination images plot_rgb;
• Plot bands of a raster quickly using plot_bands;
• Plot histograms for a set of raster files;
• Create discrete categorical legends;
• Calculate vegetation indices such as Normalized Difference Vegetation Index normalized_diff;
• Create hillshade from a DEM.

EarthPy also has an io module that allows users to

• Quickly access pre-created data subsets used in the earth-analytics courses hosted on www.earthdatascience.org;
• Download other datasets that they may want to use in their workflows.