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arxiv: 2503.20563 · v1 · pith:2LNTFXFR · submitted 2025-03-26 · cs.CV · cs.LG

TerraTorch: The Geospatial Foundation Models Toolkit

Carlos Gomes , Benedikt Blumenstiel , Joao Lucas de Sousa Almeida , Pedro Henrique de Oliveira , Paolo Fraccaro , Francesc Marti Escofet , Daniela Szwarcman , Naomi Simumba
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Romeo Kienzler Bianca Zadrozny
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Reviewed by Pithpith:2LNTFXFRopen to challenge →

classification cs.CV cs.LG
keywords terratorchmodelsfoundationgeospatialbenchmarkingdatafine-tuneintegrates
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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 at https://github.com/IBM/terratorch, and can be installed via pip install terratorch.

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