{"url":"/dataset/calcrop21","name":"CalCROP21","full_name":null,"description_markdown":"**CalCROP21** is a georeferenced multi-spectral dataset of satellite Imagery and crop labels. It is a semantic segmentation benchmark dataset, for the diverse crops in the Central Valley region of California at 10m spatial resolution using a Google Earth Engine based robust image processing pipeline.","description_withheld":null,"homepage":"https://drive.google.com/drive/folders/1EnXXRHNoTyIbM-_5p-P9pH4zH3xyTqBp","introduced_date":"2021-07-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/calcrop21-a-georeferenced-multi-spectral","title":"CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels","first_author":"Rahul Ghosh","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["CalCROP21"],"data_loaders":[],"num_papers_in_archive":2,"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."}