IBM/terramind

Earth system foundation model data, training, and eval

[CVPR26] TESSERA is a foundation model that can process time-series satellite imagery for applications such as land classification and canopy height prediction. Developed at the University of Cambridge, it enables efficient extraction of temporal patterns from Earth observation

A Python toolkit for fine-tuning Geospatial Foundation Models (GFMs).

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

Examples of using the Planetary Computer

Official release of GeoGPT models.

Earth observation processing framework for machine learning in Python

Tutorials and content created by Earth Engine users, for Earth Engine users

A curated list of Google Earth Engine resources