{"id":"W3207200417","doi":"10.1109/igarss47720.2021.9553499","title":"Global land use / land cover with Sentinel 2 and deep learning","year":2021,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1249,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"National Geographic Society","keywords":"Geospatial analysis; Land cover; Remote sensing; Computer science; Deep learning; Satellite imagery; Big data; Cloud computing; Data science; Geomatics; Earth observation; Land use; Artificial intelligence; Satellite; Cartography; Geography; Data mining; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01002611946323105,"score_gpt":0.2014934866961274,"score_spread":0.1914673672328963,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}