{"url":"/dataset/uc-merced-land-use-dataset","name":"UC Merced Land Use Dataset","full_name":null,"description_markdown":"This is a 21 class land use image dataset meant for research purposes.\r\n\r\nThere are 100 images for each of the following classes:\r\n\r\n- agricultural\r\n- airplane\r\n- baseballdiamond\r\n- beach\r\n- buildings\r\n- chaparral\r\n- denseresidential\r\n- forest\r\n- freeway\r\n- golfcourse\r\n- harbor\r\n- intersection\r\n- mediumresidential\r\n- mobilehomepark\r\n- overpass\r\n- parkinglot\r\n- river\r\n- runway\r\n- sparseresidential\r\n- storagetanks\r\n- tenniscourt\r\n- Each image measures 256x256 pixels.\r\n\r\nThe images were manually extracted from large images from the USGS National Map Urban Area Imagery collection for various urban areas around the country. The pixel resolution of this public domain imagery is 1 foot.\r\n\r\nSource: [UC Merced Land Use Dataset](http://weegee.vision.ucmerced.edu/datasets/landuse.html)","description_withheld":null,"homepage":"http://weegee.vision.ucmerced.edu/datasets/landuse.html","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Scene Classification","url":"/task/scene-classification","datasets_with_task":"/datasets/task/scene-classification"}],"languages":[],"variants":["UC Merced Land Use Dataset"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/blanchon/UC_Merced","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/tensorflow/datasets","url":"https://www.tensorflow.org/datasets/catalog/uc_merced","frameworks":["tf","jax"]}],"num_papers_in_archive":23,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/scene-classification-on-uc-merced-land-use","task":"Scene Classification","dataset_variant":"UC Merced Land Use Dataset","rows":6,"metrics":["Accuracy (%)"],"first_row_in_archive_order":{"model":"µ2Net+ (ViT-L/16)","paper":"/paper/a-continual-development-methodology-for-large","metrics":{"Accuracy (%)":"100"},"code_links":[{"title":"google-research/google-research","url":"https://github.com/google-research/google-research/tree/master/muNet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/a-continual-development-methodology-for-large","title":"A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems","date":"2022-09-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/all-grains-one-scheme-agos-learning-multi","title":"All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification","date":"2022-05-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/local-semantic-enhanced-convnet-for-aerial","title":"Local semantic enhanced convnet for aerial scene recognition","date":"2021-07-08","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/msmatch-semi-supervised-multispectral-scene","title":"MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels","date":"2021-03-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-multiple-instance-densely-connected-convnet","title":"A multiple-instance densely-connected ConvNet for aerial scene classification","date":"2020-03-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/in-domain-representation-learning-for-remote-1","title":"In-domain representation learning for remote sensing","date":"2019-11-15","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}