{"url":"/dataset/oscd","name":"OSCD","full_name":"Onera Satellite Change Detection","description_markdown":"The Onera Satellite Change Detection dataset addresses the issue of detecting changes between satellite images from different dates.\r\n\r\nIt comprises 24 pairs of multispectral images taken from the Sentinel-2 satellites between 2015 and 2018. Locations are picked all over the world, in Brazil, USA, Europe, Middle-East and Asia. For each location, registered pairs of 13-band multispectral satellite images obtained by the Sentinel-2 satellites are provided. Images vary in spatial resolution between 10m, 20m and 60m.\r\n\r\nPixel-level change ground truth is provided for all 14 training and 10 test image pairs. The annotated changes focus on urban changes, such as new buildings or new roads. These data can be used for training and setting parameters of change detection algorithms.","description_withheld":null,"homepage":"https://rcdaudt.github.io/oscd/","introduced_date":"2018-10-19","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Change Detection","url":"/task/change-detection","datasets_with_task":"/datasets/task/change-detection"}],"languages":[],"variants":["OSCD","OSCD - 3ch","OSCD - 13ch"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/blanchon/OSCD_MSI","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/blanchon/OSCD_RGB","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/change-detection-on-oscd-13ch","task":"Change Detection","dataset_variant":"OSCD - 13ch","rows":6,"metrics":["F1","Precision"],"first_row_in_archive_order":{"model":"FC-Siam-Diff","paper":"/paper/fully-convolutional-siamese-networks-for","metrics":{"F1":"57.92","Precision":"51.84"},"code_links":[{"title":"likyoo/open-cd","url":"https://github.com/likyoo/open-cd"},{"title":"Bobholamovic/CDLab","url":"https://github.com/Bobholamovic/CDLab"},{"title":"rcdaudt/fully_convolutional_change_detection","url":"https://github.com/rcdaudt/fully_convolutional_change_detection"},{"title":"kyoukuntaro/FCSN_for_ChangeDetection_IGARSS2018","url":"https://github.com/kyoukuntaro/FCSN_for_ChangeDetection_IGARSS2018"},{"title":"sbonnefoy/siamese_net_change_detection","url":"https://gitlab.com/sbonnefoy/siamese_net_change_detection"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/change-detection-on-oscd-3ch","task":"Change Detection","dataset_variant":"OSCD - 3ch","rows":6,"metrics":["F1","Precision"],"first_row_in_archive_order":{"model":"MAE+MTP(ViT-L+RVSA)","paper":"/paper/mtp-advancing-remote-sensing-foundation-model","metrics":{"F1":"55.92"},"code_links":[{"title":"vitae-transformer/mtp","url":"https://github.com/vitae-transformer/mtp"},{"title":"cuzyoung/crossearth","url":"https://github.com/cuzyoung/crossearth"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/be-the-change-you-want-to-see-revisiting","title":"Be the Change You Want to See: Revisiting Remote Sensing Change Detection Practices","date":"2025-07-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/mtp-advancing-remote-sensing-foundation-model","title":"MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining","date":"2024-03-20","rows_on_this_dataset":3,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":4,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dino-mc-self-supervised-contrastive-learning","title":"Extending global-local view alignment for self-supervised learning with remote sensing imagery","date":"2023-03-12","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/seasonal-contrast-unsupervised-pre-training","title":"Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data","date":"2021-03-30","rows_on_this_dataset":1,"code_links":5,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":0,"samples_unverified":8,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/self-supervised-pre-training-enhances-change","title":"Self-supervised pre-training enhances change detection in Sentinel-2 imagery","date":"2021-01-20","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/fully-convolutional-siamese-networks-for","title":"Fully Convolutional Siamese Networks for Change Detection","date":"2018-10-19","rows_on_this_dataset":4,"code_links":5,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":16,"samples_ran":4,"samples_unverified":12,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":2,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}