ucam-eo/geotessera

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

A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

Download and process satellite imagery in Python using Sentinel Hub services.

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

Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

A collection of tools to work with Google Earth Engine Python API

[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

Free and open source library for AI object detection and semantic segmentation in geospatial rasters. 🚀

Earth system foundation model data, training, and eval