geoplot is a high-level Python geospatial plotting library. It’s an extension to cartopy and matplotlib which makes mapping easy: like seaborn for geospatial.
The Remote Sensing and GIS software library (RSGISLib) is a collection of tools for processing remote sensing and GIS datasets. The tools are accessed using Python bindings or an XML interface.
GeoPySpark is a Python bindings library for GeoTrellis, a Scala library for working with geospatial data in a distributed environment.
On open source geometry processing library focusing on regions and moving regions.
Algorithms for constructing regions, identifying connected components, creating moving regions, and performing operations on moving regions are included.
GeoViews is a new Python library that makes it easy to explore and visualize geographical, meteorological, oceanographic, weather, climate, and other real-world data. GeoViews was developed by Continuum Analytics, in collaboration with the Met Office. GeoViews is completely open source, available under a BSD license freely for both commercial and non-commercial use, and can be obtained as described at the Github site.GeoViews is built on the HoloViews library for building flexible visualizations of multidimensional data.
GeoViews adds a family of geographic plot types, transformations, and primitives based primarily on the Cartopy library, plotted using either the Matplotlib or Bokeh packages.
The pixelscan library provides functions to scan pixels on a grid in a variety of spatial patterns. The library consists of scan generators and coordinate transformations. Scan generators are Python generators that return pixel coordinates in a particular spatial pattern. Coordinate transformations are iterators that apply spatial transformations to the coordinates created by the scan generators. Transformation can be chained to yield very generic transformations.
This package makes it simple to load geospatial data from files. Currently binary and grib1/grib2 files are supported. Data can be loaded across a range of dates, forecast hours (for forecast data), and ensemble members (for ensemble forecast data).
PyNGL (pronounced “pingle”) is a Python language module used to visualize scientific data, with an emphasis on high quality 2D visualizations.
PyNIO is a Python module used for reading and writing files in several different data formats, including netCDF, netCDF 4, GRIB1, GRIB2, HDF 4, HDF-EOS 2 and HDF-EOS5, and CCM history files.