{"url":"/dataset/chesapeakersc","name":"ChesapeakeRSC","full_name":"Chesapeake Roads Spatial Context","description_markdown":"A novel remote sensing dataset for evaluating a geospatial machine learning model's ability to learn long range dependencies and spatial context understanding. We create a task to use as a proxy for this by training models to extract roads which have been broken into disjoint pieces due to tree canopy occluding large portions of the road.\r\n\r\nThe dataset consists of 30,000 RGBN NAIP images and land cover annotations from the Chesapeake Conservacy containing significant amounts of the `Tree Canopy Over Road` category.","description_withheld":null,"homepage":"https://github.com/isaaccorley/chesapeakersc","introduced_date":"2024-01-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/seeing-the-roads-through-the-trees-a","title":"Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery","first_author":"Caleb Robinson","url":null},"license":{"name":"MIT","url":"https://github.com/isaaccorley/ChesapeakeRSC/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Road Segmentation","url":"/task/road-segementation","datasets_with_task":"/datasets/task/road-segementation"}],"languages":[],"variants":["ChesapeakeRSC"],"data_loaders":[{"repo":"https://github.com/isaaccorley/chesapeakersc","url":"https://github.com/isaaccorley/chesapeakersc","frameworks":["pytorch"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/road-segmentation-on-chesapeakersc","task":"Road Segmentation","dataset_variant":"ChesapeakeRSC","rows":4,"metrics":["DWR"],"first_row_in_archive_order":{"model":"U-Net (ResNet-18)","paper":"/paper/seeing-the-roads-through-the-trees-a","metrics":{"DWR":"46.5"},"code_links":[{"title":"isaaccorley/chesapeakersc","url":"https://github.com/isaaccorley/chesapeakersc"},{"title":"isaaccorley/resize-is-all-you-need","url":"https://github.com/isaaccorley/resize-is-all-you-need"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/seeing-the-roads-through-the-trees-a","title":"Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery","date":"2024-01-12","rows_on_this_dataset":4,"code_links":2,"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."}