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Add README
Browse files- .gitattributes +1 -0
- README.md +74 -1
- assets/examples.png +3 -0
- assets/one_degree_map.png +3 -0
- assets/timestamps.png +3 -0
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README.md
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# TerraMesh
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---
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license: CC-BY-SA-4.0
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pretty_name: "TerraMesh"
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dataset info:
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- size: "~14TB (compressed)"
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- samples: "≈9.1M train / 89k val"
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- patch size: "264x264 pixel"
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- temporal coverage: "2017→2024"
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---
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# TerraMesh
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> **A planetary‑scale, multimodal analysis‑ready dataset for Earth‑Observation foundation models.**
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**TerraMesh** merges data from **Sentinel‑1 SAR, Sentinel‑2 optical, Copernicus DEM, NDVI and land‑cover** sources into more than **9 million co‑registered patches** ready for large‑scale representation learning. Compared with earlier public corpora it offers **>20×** more pixel values and truly global, multi‑season coverage.
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> ** Dataset release – End of June. **
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---
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## Key features
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| Aspect | Value |
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| ---------- |--------------------------------------------------------------------------------------------------------------------------------|
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| Modalities | S‑2 L1C (13 bands), S‑2 L2A (12 bands), S‑2 RGB (3 bands), S‑1 GRD (VV, VH), S‑1 RTC (VV, VH), NDVI, Copernicus DEM, ESRI LULC |
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| Samples | **9 089 536** train · **89 088** val |
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| Patch size | 264 × 264 pixel (10 m grid) |
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| Years | 2017 – 2024 (peak 2019 ‑ 2023) |
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| License | CC‑BY‑SA‑4.0 |
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---
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## Dataset organisation
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The archive ships two top‑level splits `train/` and `val/`, each holding one folder per modality. More details with the dataset release end of June.
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---
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## Global coverage & class distribution
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---
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## Performance evaluation
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[radar.pdf](assets%2Fradar.pdf)
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---
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## Citation
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If you use TerraMesh, please cite:
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```bibtex
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@article{blumenstiel2025terramesh,
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title={Terramesh: A planetary mosaic of multimodal earth observation data},
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author={Blumenstiel, Benedikt and Fraccaro, Paolo and Marsocci, Valerio and Jakubik, Johannes and Maurogiovanni, Stefano and Czerkawski, Mikolaj and Sedona, Rocco and Cavallaro, Gabriele and Brunschwiler, Thomas and Bernabe-Moreno, Juan and others},
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journal={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
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year={2025}
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}
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```
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---
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## License
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TerraMesh is released under the **Creative Commons Attribution‑ShareAlike 4.0 (CC‑BY‑SA‑4.0)** license.
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---
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## Acknowledgements
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TerraMesh is part of the **FAST‑EO** project funded by the European Space Agency Φ‑Lab (contract #4000143501/23/I‑DT) and builds upon SSL4EO‑S12 and MajorTOM‑Core datasets.
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---
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assets/examples.png
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Git LFS Details
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assets/one_degree_map.png
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Git LFS Details
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assets/timestamps.png
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Git LFS Details
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