Python
Python Packages
This list of Python packages is adapted from the Python list of Awesome Geospatial.
Geospatial Analysis
- whitebox - A Python package for advanced geospatial data analysis based on WhiteboxTools.
- lidar - lidar is a toolset for terrain and hydrological analysis using digital elevation models (DEMs).
- pygis - pygis is a collection of Python snippets for geospatial analysis.
- ArcGIS Python API - Esri's Python library for working with maps and geospatial data, powered by web GIS.
- dask-rasterio - Read and write rasters in parallel using Rasterio and Dask.
- earthengine-api - The Earth Engine Python API allows developers to interact with Google Earth Engine.
- EarthPy - EarthPy is a python package that makes it easier to plot and work with spatial raster and vector data.
- Fiona - For making it easy to read/write geospatial data formats.
- GDAL - The Geospatial Data Abstraction Library for reading and writing raster and vector geospatial data formats.
- geeup - Simple CLI for Earth Engine Uploads.
- geojson-area - Calculate the area inside of any GeoJSON geometry. This is a port of Mapbox's geojson-area for Python.
- geojsonio - Open GeoJSON data on geojson.io from Python.
- GeoPandas - Python tools for geographic data.
- GIPPY - Geospatial Image Processing for Python.
- gpdvega - gpdvega is a bridge between GeoPandas and Altair that allows to seamlessly chart geospatial data.
- mapboxgl-jupyter - Use Mapbox GL JS to visualize data in a Python Jupyter notebook.
- networkx - To work with networks.
- OSMnet - Tools for the extraction of OpenStreetMap street network data.
- pandana - Pandas Network Analysis - dataframes of network queries, quickly.
- Peartree - Peartree: A library for converting transit data into a directed graph for network analysis.
- pygdal - Virtualenv and setuptools friendly version of standard GDAL python bindings.
- pymap3d - Python 3D coordinate conversions for geospace ecef enu eci.
- Pyncf - Pure Python NetCDF file reading and writing.
- PyProj - For conversions between projections.
- PySAL - For all your spatial econometrics needs.
- PyShp - For reading and writing shapefiles.
- rasterio - rasterio employs GDAL under the hood for file I/O and raster formatting.
- rasterstats - Python module for summarizing geospatial raster datasets based on vector geometries.
- rio-cogeo - CloudOptimized GeoTIFF creation plugin for rasterio.
- rio-color - Color correction plugin for rasterio.
- rio-hist - Histogram matching plugin for rasterio.
- rio-tiler - Get mercator tile from landsat, sentinel or other AWS hosted raster.
- Rtree - For efficiently querying spatial data.
- sentinelhub - Download and process satellite imagery in Python scripts using Sentinel Hub services.
- sentinelsat - Search and download Copernicus Sentinel satellite images.
- Shapely - Manipulation and analysis of geometric objects in the Cartesian plane.
- ts-raster - ts-raster is a python package for analyzing time-series characteristics from raster data.
- urbansim - New version of UrbanSim, a platform for modeling metropolitan real estate markets.
- USGS API - USGS is a python module for interfacing with the US Geological Survey's API.
- Verde - Verde is a Python library for processing spatial data and interpolating it on regular grids.
- xarray - An open source project that aims to bring the labeled data power of pandas to the physical sciences.
Mapping/Plotting
- basemap - Plot on map projections (with coastlines and political boundaries) using matplotlib.
- bokeh - Interactive Web Plotting for Python.
- Cartopy - A library providing cartographic tools for python for plotting spatial data.
- Descartes - Plot geometries in matplotlib.
- geoplot - geoplot is a high-level Python geospatial plotting library.
- geopy - geopy is a Python 2 and 3 client for several popular geocoding web services.
- folium - Python Data, Leaflet.js Maps.
- matplotlib - Python 2D plotting library.
- mplleaflet - mplleaflet converts a matplotlib plot into a webpage containing a pannable, zoomable Leaflet map.
- pyWPS - An implementation of the Web Processing Service standard from the Open Geospatial Consortium.
- pyCSW - Fully implements the OpenGIS Catalogue Service Implementation Specification.
- ipyleaflet - A Jupyter / Leaflet bridge enabling interactive maps in the Jupyter notebook.
Deep Learning
- label-maker - Data Preparation for Satellite Machine Learning.
- label-maker-binder - Using label-maker in an interactive notebook on the cloud.
- Keras - Keras is a high-level neural networks API capable of running on top of TensorFlow, CNTK, or Theano.
- TensorFlow - TensorFlow is an open source software library for numerical computation using data flow graphs.
General Python
- dask - Dask is a flexible parallel computing library for analytics.
- imageio - imageio provides an easy interface to read and write a wide range of image data.
- Mahotas - Mahotas is a library of fast computer vision algorithms operating over numpy arrays.
- NumPy - NumPy is the fundamental package for scientific computing with Python.
- Pandas - Open source library providing high-performance, easy-to-use data structures and data analysis tools.
- scikit-image - Scikit-image is a collection of algorithms for image processing.
- scikit-learn - scikit-learn is a Python module for machine learning built on top of SciPy.
- SciPy - SciPy is open-source software for mathematics, science, and engineering.
- Statsmodels - Python module that allows users to explore data, estimate statistical models, and perform statistical tests.
Cloud Computing Platforms
- Google Earth Engine - Planetary-scale geospatial analysis for everyone.
- Pangeo - A community platform for Big Data geoscience.
- Geospatial Big Data Platform (GBDX) - Cloud computing platform from Digital Globe.
- Radiant Earth - Open-source cloud computing infrastructure for geospatial analysis.
- Radiant MLHub - Open Repository for Geospatial Training Data.
- Sentinel Playground - Cloud platform for analysis of Sentinel-2A and B and so on.
- Vane: Query Language - Creating Basemaps from different satellite images with online processing and computing.