{
 "id": "embed2scale/SSL4EO-S12-v1.1",
 "owner": "embed2scale",
 "name": "SSL4EO-S12-v1.1",
 "downloads": 7014,
 "likes": 5,
 "last_modified": "2026-07-22T11:59:08.000Z",
 "stated_licence": "cc-by-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "feature-extraction"
 ],
 "citation": "If you use this dataset in your work, please cite:\n```txt\n@article{blumenstiel2025ssl4eos12,\n  title={{SSL4EO-S12} v1.1: A Multimodal, Multiseasonal Dataset for Pretraining, Updated},\n  author={Blumenstiel, Benedikt and Ait Ali Braham, Nassim and Albrecht, Conrad M and Maurogiovanni, Stefano and Fraccaro, Paolo},\n  journal={arXiv preprint arXiv:2503.00168},\n  year={2025}\n}\n```\n\nThis dataset is an updated version of:\n```text\n@article{wang2022ssl4eo,\n  title={{SSL4EO-S12}: A large-scale multimodal, multitemporal dataset for self-supervised learning in Earth observation [Software and Data Sets]},\n  author={Wang, Yi and Ait Ali Braham, Nassim and Xiong, Zhitong and Liu, Chenying and Albrecht, Conrad M and Zhu, Xiao Xiang},\n  journal={IEEE Geoscience and Remote Sensing Magazine},\n  volume={11},\n  number={3},\n  pages={98--106},\n  year={2023},\n  publisher={IEEE}\n}\n```",
 "signal": "permissive",
 "reason": "The declared licence (cc-by-4.0) is classified as permissive.",
 "revision": "97a91733db962222e1e6b40a836845ddbbb16b86",
 "stated_evidence": "https://huggingface.co/datasets/embed2scale/SSL4EO-S12-v1.1/blob/97a91733db962222e1e6b40a836845ddbbb16b86/README.md",
 "file_evidence": "https://huggingface.co/datasets/embed2scale/SSL4EO-S12-v1.1/tree/97a91733db962222e1e6b40a836845ddbbb16b86",
 "card_nc": false
}