A curated list of geospatial tools, data, tutorials, information, and more
Various awesome tools for geospatial work
- QGIS: A Free and Open Source Geographic Information System - Awesome for viewing raster and vector data
- GIMP: For editing visual (non-analytic) raster products
- GeoJSON.io: Online GeoJSON viewer/editor
Awesome libraries to support geospatial development
- GDAL: Geospatial Data Abstraction Library - C/C++ library with Python bindings and helpful command line tools for handling many raster and vector geospatial data formats
- Rasterio: Python package for reading/writing raster datasets, based on GDAL
- Shapely: Python package for manipulation and analysis of planar geometric objects, based on GEOS
- GEOS: GEOS (Geometry Engine - Open Source) is a C++ port of the Java Topology Suite (JTS)
Data that is publicly available at no extra cost (access fees may apply for AWS/GCP)
- Copernicus: European Space Agency (ESA) provides vast amounts of public data, most notably Sentinel-1 for radar and Sentinel-2 for optical satellite data.
- Landsat: Earth-observation satellites from the USGS.
- AWS Earth: Amazon Web Services (AWS) provides several datasets, including Landsat 8, Sentinel-2, NEXRAD, OpenStreetMap, and more.
- Planet Open California: Planet's open dataset over California as CC-BY-SA license
- GIS StackExchange - Q&A site for Geospatial questions
- Gunter's Space Page - Info about spacecraft, launch vehicles, and launches
- GDAL Cheat Sheet - Cheat sheet for GDAL/OGR command-line tools
- Python GDAL/OGR Cookbook - Simple code snippets on how to use the Python GDAL/OGR API
- A Gentle Introduction to GDAL: A multi-part series on GDAL by Robert Simmon of Planet
- An Introduction to GDAL: A talk giving an awesome introduction to GDAL by Robert Simmon of Planet (at OpenVisConf 2017)
- Python from Space: Analyzing Open Satellite Imagery Using the Python Ecosystem: Using Jupyter notebooks to do awesome thigns with satellite imagery by Katherine Scott of Planet (at PyCon 2017)
Contributions welcome! Read the contribution guidelines first.
To the extent possible under law, Jeremy Mayeres has waived all copyright and related or neighboring rights to this work.