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| title: README | |
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| IBM and ESA 🌍 Advancing Geospatial AI with TerraMind | |
| IBM and the European Space Agency (ESA) Φ-lab introduce TerraMind, the first multimodal, any-to-any generative foundation model for Earth Observation. | |
| TerraMind reaches new SOTA results on downstream tasks and introduces the "Thinking-in-Modalities" approach to handle missing modalities. | |
| The model was pre-trained in partnership with Jülich Supercomputing Centre (Forschungszentrum Jülich) and supported by the FAST-EO project. | |
| 🤝 Open Source | |
| The FAST-EO partners and ESA Φ-lab are committed to Open Source, sharing knowledge, and driving innovation for the geospatial domain. | |
| 📚 Papers and Resources | |
| Explore the technical paper detailing TerraMind's architecture and applications [here](https://arxiv.org/abs/2504.11171). | |
| 📊 Upcoming Models and Datasets | |
| Stay tuned for our upcoming model and dataset releases: [Llama3-MS-CLIP](https://arxiv.org/abs/2503.15969) and [TerraMesh](https://arxiv.org/abs/2504.11172). | |
| 🚀 Challenge | |
| Already working with TerraMind? Submit your use case to the [TerraMind Blue-Sky Challenge](https://huggingface.co/spaces/ibm-esa-geospatial/challenge), a bi-monthly award spotlighting the boldest, most imaginative ways using TerraMind. | |
| Explore our models, datasets, and papers, and join our discussions to shape the future of geospatial AI! | |