TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data. It integrates domain-specific data modules, pre-defined tasks, and a modular model factory that pairs any backbone with diverse decoder heads. These components allow researchers and practitioners to fine-tune supported models in a no-code fashion by simply editing a training configuration. By consolidating best practices for model development and incorporating the automated hyperparameter optimization extension Iterate, TerraTorch reduces the expertise and time required to fine-tune or benchmark models on new Earth Observation use cases. Furthermore, TerraTorch directly integrates with GEO-Bench, allowing for systematic and reproducible benchmarking of Geospatial Foundation Models. TerraTorch is open sourced under Apache 2.0, available atthis https URL, and can be installed via pip install terratorch.
View on arXiv@article{gomes2025_2503.20563,
title={ TerraTorch: The Geospatial Foundation Models Toolkit },
author={ Carlos Gomes and Benedikt Blumenstiel and Joao Lucas de Sousa Almeida and Pedro Henrique de Oliveira and Paolo Fraccaro and Francesc Marti Escofet and Daniela Szwarcman and Naomi Simumba and Romeo Kienzler and Bianca Zadrozny },
journal={arXiv preprint arXiv:2503.20563},
year={ 2025 }
}