Geospatial Tools

This is a list of geospatial tools and libraries.

📖 Geospatial lists

Name	GitHub Repository	Description
Awesome Geospatial	GitHub link	Long list of geospatial analysis tools. Geospatial analysis, or just spatial analysis, is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect.
satellite-image-deep-learning	GitHub link	This repository lists resources on the topic of deep learning applied to satellite and aerial imagery. To a lesser extent classical machine learning techniques are listed, as are topics such as cloud computing and model deployment.
awesome-gee-community-datasets	GitHub link	The awesome-gee-community-datasets are community-sourced geospatial datasets made available for use by the larger Google Earth Engine community and shared publicly as Earth Engine assets.
Awesome Earth Engine	GitHub link	A curated list of Google Earth Engine resources. Please visit the Awesome-GEE GitHub repo if you want to contribute to this project.
Awesome-EarthObservation-Code	GitHub link	A curated list of awesome tools, tutorials, code, helpful projects, links, stuff about Earth Observation and Geospatial stuff.

🛰️ Earth Observation

Name	Documentation	GitHub Repository	Description
Raster4ML	Doc link	GitHub link	Raster4ML is a python package that extracts machine learning ready dataset from geospatial raster data and shapefiles. The package aims to aid geospatial researchers and scientists to extract meaningful faetures easily and focus more on the model training or reproducibility issues.
ee	Doc link	GitHub link	Python and JavaScript client libraries for calling the Google Earth Engine API.
geemap	Doc link	GitHub link	A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets.
eemont	Doc link	GitHub link	A Python package that extends Google Earth Engine.
EODAG	Doc link	GitHub link	EODAG (Earth Observation Data Access Gateway) is a command line tool and a plugin-oriented Python framework for searching, aggregating results and downloading remote sensed images while offering a unified API for data access regardless of the data provider.
RSGISLib	Doc link	GitHub link	The Remote Sensing and GIS software library (RSGISLib) is a collection of tools for processing remote sensing and GIS datasets.
sentinelhub	Doc link	GitHub link	The sentinelhub Python package is the official Python interface for Sentinel Hub services. It supports most of the services described in the Sentinel Hub documentation and any type of satellite data collections, including Sentinel, Landsat, MODIS, DEM, and custom collections produced by users.
EOEPCA System	Doc link	GitHub link	"A selection of building blocks are available, addressing the three key domains identified in the architecture: Resource Management - catalogue and discovery of data and applications. Processing and Chaining - deployment and execution of applications. User Management - identity, security, access control and accounting"
MetPy	Doc link	GitHub link	MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.
Museo ToolBox	Doc link	GitHub link	Museo ToolBox is a python library to simplify the use of raster/vector, especially for machine learning and remote sensing. It is now easy to extract raster values from vector polygons and to do some spatial/unspatial cross-validation for scikit-learn from raster.
rastervision	Doc link	GitHub link	Raster Vision is an open source Python library and framework for building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery).
EOReader	Doc link	GitHub link	EOReader is a remote-sensing opensource python library reading optical and SAR constellations, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

🌎 GIS

Name	Documentation	GitHub Repository	Description
geopandas	Doc link	GitHub link	GeoPandas is a project to add support for geographic data to pandas objects.
MGWR	-	GitHub link	This module provides functionality to calibrate multiscale (M)GWR as well as traditional GWR. It is built upon the sparse generalized linear modeling (spglm) module.
Shapely	Doc link	GitHub link	Manipulation and analysis of geometric objects in the Cartesian plane.
rasterio	Doc link	GitHub link	Rasterio reads and writes geospatial raster data.
rasterstats	Doc link	GitHub link	Python module for summarizing geospatial raster datasets based on vector geometries. It includes functions for zonal statistics and interpolated point queries.
WhiteboxTools	Doc link	GitHub link	WhiteboxTools is an advanced geospatial data analysis platform.
whiteboxgui	Doc link	GitHub link	The whiteboxgui Python package is a Jupyter frontend for WhiteboxTools, an advanced geospatial data analysis platform.
pysal	Doc link	GitHub link	PySAL, the Python spatial analysis library, is an open source cross-platform library for geospatial data science with an emphasis on geospatial vector data written in Python.
pykrige	Doc link	GitHub link	Kriging Toolkit for Python.
geostat framework	Doc link	GitHub link	GeoStatTools is a library providing geostatistical tools like kriging, random field generation, variogram estimation, covariance models and much more.
gstools	Doc link	GitHub link	GeoStatTools provides geostatistical tools for various purposes.
Spatialpandas	Doc link	GitHub link	Spatialpandas provides Pandas and Dask extensions for vectorized spatial and geometric operations, such as fast, spatially indexed rendering of large collections of polygons, lines, or points.
GeoParquet	Doc link	GitHub link	This repository defines how to store geospatial vector data (point, lines, polygons) in Parquet, a popular columnar storage format for tabular data.
SciKit GStat	Doc link	GitHub link	SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes two base classes Variogram and OrdinaryKriging. Additionally, various variogram classes inheriting from Variogram are available for solving directional or space-time related tasks.
R terra	Doc link	GitHub link	terra is an R package for spatial data analysis. Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include standard operations such as intersect and buffer. Raster methods include global, local, zonal, and focal computations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported.

💻 Data Science & Machine Learning/Deep Learning

Name	Documentation	GitHub Repository	Description
SHAP	Doc link	GitHub link	SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions.
gradio	Doc link	GitHub link	Gradio is an open-source Python library that is used to build machine learning and data science demos and web applications.
Torchgeo	Doc link	GitHub link	TorchGeo is a PyTorch domain library, similar to torchvision, providing datasets, samplers, transforms, and pre-trained models specific to geospatial data.

⚙️ Interactivity & Visualization

Name	Documentation	GitHub Repository	Description
leafmap	Doc link	GitHub link	A Python package for geospatial analysis and interactive mapping in a Jupyter environment.
ipyleaflet	Doc link	GitHub link	A Jupyter / Leaflet bridge enabling interactive maps in the Jupyter notebook.
ipywidgets	Doc link	GitHub link	ipywidgets, also known as jupyter-widgets or simply widgets, are interactive HTML widgets for Jupyter notebooks and the IPython kernel.
folium	Doc link	GitHub link	folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium.
voilà	Doc link	GitHub link	Rendering of live Jupyter notebooks with interactive widgets.
pyvista	Doc link	GitHub link	PyVista is a helper module for the Visualization Toolkit (VTK) that wraps the VTK library through NumPy and direct array access through a variety of methods and classes. This package provides a Pythonic, well-documented interface exposing VTK's powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets.
kepler.gl	Doc link	GitHub link	Kepler.gl is a data-agnostic, high-performance web-based application for visual exploration of large-scale geolocation data sets. Built on top of Mapbox GL and deck.gl, kepler.gl can render millions of points representing thousands of trips and perform spatial aggregations on the fly.
Datashader	Doc link	GitHub link	Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.
HoloViews	Doc link	GitHub link	HoloViews is an open-source Python library designed to make data analysis and visualization seamless and simple. With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting.
Panel	Doc link	GitHub link	Panel provides tools for easily composing widgets, plots, tables, and other viewable objects and controls into custom analysis tools, apps, and dashboards. Panel works with visualizations from Altair, Bokeh, HoloViews, Matplotlib, Plotly, pydeck, PyVista and many other Python plotting libraries, making them instantly viewable either individually or when combined with interactive widgets that control them.
Mito Spreadsheets	Doc link	GitHub link	Mito is a spreadsheet that lives inside your JupyterLab notebooks. It allows you to edit Pandas dataframes like an Excel file, and generates Python code that corresponds to each of your edits.
plotly	Doc link	GitHub link	Plotly's Python graphing library makes interactive, publication-quality graphs.

📷 3D

Name	Documentation	GitHub Repository	Description
open3d	Doc link	GitHub link	Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization.

🔧 Other Python libraries

Name	Documentation	GitHub Repository	Description
JupyterBook	Doc link	GitHub link	Jupyter Book is an open-source tool for building publication-quality books and documents from computational material.
xarray	Doc link	GitHub link	xarray (formerly xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays.
xarray-spatial	Doc link	GitHub link	Xarray-Spatial implements common raster analysis functions using Numba and provides an easy-to-install, easy-to-extend codebase for raster analysis. xarray-spatial does not depend on GDAL / GEOS, which makes it fully extensible in Python but does limit the breadth of operations that can be covered.
rioxarray	Doc link	GitHub link	rioxarray extends xarray with the rio accessor.
Dask	Doc link	GitHub link	Dask is a flexible parallel computing library for analytics.
Geospatial	Doc link	GitHub link	A Python package for installing commonly used packages for geospatial analysis and data visualization with only one command.

Other useful tools

Name	Documentation	GitHub Repository	Description
MapColPal	Doc link	GitHub link	This tool is here to help you work with color palettes for thematic maps.

Websites

Name	Link	Description
Sentinel-2 UTM Tiling Grid (ESA)	Link	This dataset shows the tiling grid and their IDs for Sentinel 2 satellite imagery. The tiling grid IDs are useful for selecting imagery of an area of interest.
Spectator Earth	Link	Real-Time Satellite Position Monitoring and Imagery Access.

Training

GIS & Earth Observation

Name	Link	Description
E-TRAINEE	Link	E-learning course on Time Series Analysis in Remote Sensing for Understanding Human-Environment Interactions (E-TRAINEE) was developed by collaboration of research groups from four partner universities – Charles University, Heidelberg University, University of Innsbruck, and University of Warsaw within the ERASMUS+ Strategic partnership project (ID 2020-1-CZ01-KA203-078308).
WEkEO	Link	Trainings provided by WEkEO DIAS.
Data Carpentry	Link	Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.
Trainings list - EUMETSAT	Link	List of trainings and tutorials available from EUMETSAT.
Data Access Services - EUMETSAT	Link	Tutorials and trainings about Data Access Services provided by EUMETSAT platform.
EUMETSAT Atlassian	Link	Information about EUMETSAT services, products, data format etc.
RUS Copernicus (Research and User Support)	Link	Trainings sessions and webinars provided by RUS Service.
EUMETSAT Training HUB - Jupyter Notebooks	Link	Jupyter notebooks available for satellite data processing and visualization.
Copernicus CAMS & C3S Jupyter Notebooks	Link	This repository hosts Jupyter notebook training material for the Copernicus Climate Change Service (C3S) and the Copernicus Atmosphere Monitoring Service (CAMS).
LTPy - a Jupyter-based Learning Tool for Atmospheric Composition Datas	Link	LTPy is based on Jupyter notebooks and has a modular approach, with learning modules on data access, data processing, data visualization and a set of example workflows to support relevant atmospheric applications.
NASA Arset Trainings	Link	NASA Arset Training list related to multiple topics.
Copernicus Land Interactive Notebooks - Terrascope service	Link	Interactive notebooks from Copernicus Land Terrascope.
geemap/leafmap tutorials	Link	Youtube tutorial about geemap/leafmap and other tools/software.
ACGeospatial	Link	Earth Observation, Geospatial, GIS, Satellite imagery, Python, Julia, courses, training.
Pratt SAVI 810 - Intro to Python Scripting for Geospatial	Link	Introduction to Python Scripting for Geospatial analysis.
S5P-Tools	Link	Scripts to download and process air-pollution data collected by the satellite Sentinel-5P from the Copernicus Open Access Hub. The collect is based on the sentinelsat package and the API Hub Access. L3 resampling is made with HARP tools.
COURSE: Artificial Intelligence (AI) for Earth Monitoring	Link	Explore how artificial intelligence (AI) and machine learning (ML) technologies are helping to advance Earth monitoring.
EUMETlab	Link	This page contains groups of code repositories that have been made open to the public by EUMETSAT and our collaborators.

Computer Science

Name	Link	Description
Computer Science courses	Link	Computer Science courses with video lectures.