{"url":"/dataset/pastis","name":"PASTIS","full_name":"Panoptic Segmentation of satellite image TImes Series","description_markdown":"PASTIS is a benchmark dataset for panoptic and semantic segmentation of agricultural parcels from satellite image time series. It is composed of 2433 one square kilometer-patches in the French metropolitan territory for which sequences of satellite observations are assembled into a four-dimensional spatio-temporal tensor. The dataset contains both semantic and instance annotations, assigning to each pixel a semantic label and an instance id. There is an official 5 fold split provided in the dataset's metadata.\r\n\r\nImage source: [https://github.com/VSainteuf/pastis-benchmark](https://github.com/VSainteuf/pastis-benchmark)","description_withheld":null,"homepage":"https://github.com/VSainteuf/pastis-benchmark","introduced_date":"2021-07-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/panoptic-segmentation-of-satellite-image-time","title":"Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks","first_author":"Vivien Sainte Fare Garnot","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Panoptic Segmentation","url":"/task/panoptic-segmentation","datasets_with_task":"/datasets/task/panoptic-segmentation"}],"languages":[],"variants":["PASTIS"],"data_loaders":[{"repo":"https://github.com/VSainteuf/pastis-benchmark","url":"https://github.com/VSainteuf/pastis-benchmark","frameworks":["pytorch"]}],"num_papers_in_archive":18,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/panoptic-segmentation-on-pastis","task":"Panoptic Segmentation","dataset_variant":"PASTIS","rows":3,"metrics":["PQ","RQ","SQ"],"first_row_in_archive_order":{"model":"Exchanger+Mask2Former","paper":"/paper/rethinking-the-encoding-of-satellite-image","metrics":{"PQ":"52.6","RQ":"61.6","SQ":"84.6"},"code_links":[{"title":"TotalVariation/Exchanger4SITS","url":"https://github.com/TotalVariation/Exchanger4SITS"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/semantic-segmentation-on-pastis","task":"Semantic Segmentation","dataset_variant":"PASTIS","rows":3,"metrics":["Mean IoU (test)","Number of Params","Overall Accuracy"],"first_row_in_archive_order":{"model":"Exchanger+Mask2Former","paper":"/paper/rethinking-the-encoding-of-satellite-image","metrics":{"Mean IoU (test)":"67.9"},"code_links":[{"title":"TotalVariation/Exchanger4SITS","url":"https://github.com/TotalVariation/Exchanger4SITS"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rethinking-the-encoding-of-satellite-image","title":"Revisiting the Encoding of Satellite Image Time Series","date":"2023-05-03","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/panoptic-segmentation-of-satellite-image-time","title":"Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks","date":"2021-07-16","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":11,"samples_ran":10,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":1,"samples_harvested":11,"samples_ran":10,"samples_unverified":1,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"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."}