{"url":"/dataset/spacenet-2","name":"SpaceNet 2","full_name":"SpaceNet 2: Building Detection v2","description_markdown":"*SpaceNet 2: Building Detection v2* - is a dataset for building footprint detection in geographically diverse settings from very high resolution satellite images. It contains over 302,701 building footprints, 3/8-band Worldview-3 satellite imagery at 0.3m pixel res., across 5 cities (Rio de Janeiro, Las Vegas, Paris, Shanghai, Khartoum), and covers areas that are both urban and suburban in nature. The dataset was split using 60%/20%/20% for train/test/validation.\r\n\r\nThe main use case for the detection of building footprints from satellite imagery is to aid foundational mapping.","description_withheld":null,"homepage":"https://spacenet.ai/spacenet-buildings-dataset-v2/","introduced_date":"2018-07-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/spacenet-a-remote-sensing-dataset-and","title":"SpaceNet: A Remote Sensing Dataset and Challenge Series","first_author":"Adam Van Etten","url":null},"license":{"name":"CC BY-SA 4.0","url":"https://creativecommons.org/licenses/by-sa/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["SpaceNet 2"],"data_loaders":[{"repo":"https://github.com/microsoft/torchgeo","url":"https://torchgeo.readthedocs.io/en/latest/api/datasets.html#torchgeo.datasets.SpaceNet2","frameworks":["pytorch"]}],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-on-spacenet-2","task":"Object Detection","dataset_variant":"SpaceNet 2","rows":2,"metrics":["F1 Score (Avg. over Cities)"],"first_row_in_archive_order":{"model":"YOLT","paper":"/paper/spacenet-a-remote-sensing-dataset-and","metrics":{"F1 Score (Avg. over Cities)":"0.60"},"code_links":[{"title":"avanetten/avanetten.github.io","url":"https://github.com/avanetten/avanetten.github.io"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/spacenet-a-remote-sensing-dataset-and","title":"SpaceNet: A Remote Sensing Dataset and Challenge Series","date":"2018-07-03","rows_on_this_dataset":2,"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."}