{"url":"/dataset/burned-area-delineation-from-satellite","name":"Burned Area Delineation from Satellite Imagery","full_name":"A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery","description_markdown":"The dataset contains 73 satellite images of different forests damaged by wildfires across Europe with a resolution of up to 10m per pixel. Data were collected from the Sentinel-2 L2A satellite mission and the target labels were generated from the Copernicus Emergency Management Service (EMS) annotations, with five different severity levels, ranging from undamaged to completely destroyed.","description_withheld":null,"homepage":"https://dl.acm.org/doi/10.1145/3511808.3557528","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"severity prediction","url":"/task/severity-prediction","datasets_with_task":"/datasets/task/severity-prediction"}],"languages":[],"variants":["Burned Area Delineation from Satellite Imagery"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/severity-prediction-on-burned-area","task":"severity prediction","dataset_variant":"Burned Area Delineation from Satellite Imagery","rows":1,"metrics":["RMSE"],"first_row_in_archive_order":{"model":"DS-UNet","paper":"/paper/attention-to-fires-multi-channel-deep","metrics":{"RMSE":"1.30"},"code_links":[{"title":"dbdmg/rescue","url":"https://github.com/dbdmg/rescue"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/attention-to-fires-multi-channel-deep","title":"Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction","date":"2021-11-22","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"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."}