{"url":"/dataset/msaw","name":"MSAW","full_name":"Multi-Sensor All Weather Mapping","description_markdown":"Multi-Sensor All Weather Mapping (MSAW) is a dataset and challenge, which features two collection modalities (both SAR and optical). The dataset and challenge focus on mapping and building footprint extraction using a combination of these data sources. MSAW covers 120 km^2 over multiple overlapping collects and is annotated with over 48,000 unique building footprints labels, enabling the creation and evaluation of mapping algorithms for multi-modal data. \r\n\r\nSource: [SpaceNet 6: Multi-Sensor All Weather Mapping Dataset](https://arxiv.org/pdf/2004.06500)","description_withheld":null,"homepage":"https://spacenet.ai/","introduced_date":"2020-04-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/spacenet-6-multi-sensor-all-weather-mapping","title":"SpaceNet 6: Multi-Sensor All Weather Mapping Dataset","first_author":"Jacob Shermeyer","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"The Semantic Segmentation Of Remote Sensing Imagery","url":"/task/the-semantic-segmentation-of-remote-sensing","datasets_with_task":"/datasets/task/the-semantic-segmentation-of-remote-sensing"},{"name":"Disaster Response","url":"/task/disaster-response","datasets_with_task":"/datasets/task/disaster-response"}],"languages":[],"variants":["MSAW"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/the-semantic-segmentation-of-remote-sensing-1","task":"The Semantic Segmentation Of Remote Sensing Imagery","dataset_variant":"MSAW","rows":1,"metrics":["F1 score"],"first_row_in_archive_order":{"model":"DeepMAO","paper":"/paper/deepmao-deep-multi-scale-aware-overcomplete","metrics":{"F1 score":"59.92"},"code_links":[{"title":"Sumanth181099/DeepMAO","url":"https://github.com/Sumanth181099/DeepMAO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/deepmao-deep-multi-scale-aware-overcomplete","title":"DeepMAO: Deep Multi-scale Aware Overcomplete Network for Building Segmentation in Satellite Imagery","date":"2023-08-14","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."}