{"url":"/dataset/gid","name":"GID","full_name":"Gaofen Image Dataset","description_markdown":"Gaofen Image Dataset (GID) is a large-scale land-cover dataset constructed with Gaofen-2 (GF-2) satellite images. This dataset has superiorities over the existing land-cover dataset because of its large coverage, wide distribution, and high spatial resolution. It contains 150 GF-2 images annotated at the pixel level for 5 categories: built-up, farmland, forest, meadow, and water.","description_withheld":null,"homepage":"https://x-ytong.github.io/project/GID.html","introduced_date":"2018-07-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-transferable-deep-models-for-land","title":"Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models","first_author":"Xin-Yi Tong","url":null},"license":{"name":"Open Source","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":"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":"Segmentation Of Remote Sensing Imagery","url":"/task/segmentation-of-remote-sensing-imagery","datasets_with_task":"/datasets/task/segmentation-of-remote-sensing-imagery"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GID"],"data_loaders":[],"num_papers_in_archive":27,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}