--- tags: - geospatial pretty_name: S2-100K --- # Dataset Card for S2-100K > The S2-100K dataset is a dataset of 100,000 multi-spectral satellite images sampled from Sentinel-2 via the Microsoft Planetary Computer. Copernicus Sentinel data is captured between Jan 1, 2021 and May 17, 2023. The dataset is sampled approximately uniformly over landmass and only includes images without cloud coverage. The dataset is available for research purposes only. If you use the dataset, please cite our paper. More information on the dataset can be found in our paper. See this [GitHub repo](https://github.com/microsoft/satclip/) for more details. ## Dataset Details ### Dataset Description > SatCLIP trains location and image encoders via contrastive learning, by matching images to their corresponding locations. This is analogous to the CLIP approach, which matches images to their corresponding text. > Through this process, the location encoder learns characteristics of a location, as represented by satellite imagery. - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses ### Direct Use To download the dataset you can use the `huggingface_hub` library. ```python from huggingface_hub import snapshot_download snapshot_download("davanstrien/satclip", local_dir='.', repo_type='dataset') ``` Alternatively you can run ```bash # Make sure you have git-lfs installed (https://git-lfs.com) git lfs install git clone https://huggingface.co/datasets/davanstrien/satclip ``` To extract the images you can run the following command. ```bash ls images/*.tar.xz |xargs -n1 tar xf ``` ## Citation **BibTeX:** ``` @article{klemmer2023satclip, title={SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery}, author={Klemmer, Konstantin and Rolf, Esther and Robinson, Caleb and Mackey, Lester and Ru{\ss}wurm, Marc}, journal={arXiv preprint arXiv:2311.17179}, year={2023} } ```