机译:Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators
Agroecosystem Sustainability Center Institute for Sustainability Energy Environment University of Illinois at Urbana Champaign||College of Agricultural Consumer and Environmental Sciences University of Illinois at Urbana Champaign;
Agroecosystem Sustainability Center Institute for Sustainability Energy Environment University of Illinois at Urbana ChampaignAgroecosystem Sustainability Center Institute for Sustainability Energy Environment University of Illinois at Urbana Champaign||C;
Agroecosystem Sustainability Center Institute for Sustainability Energy Environment University of Illinois at Urbana Champaign||College of Agricultural Consumer and Environmental Sciences University of Illinois at Urbana Champaign||National Center for SupDepartment of Forest and Wildlife Ecology University of Wisconsin-MadisonDepartment of Water Resources (WRS) Faculty of Geo-Information Science and Earth Observation (ITC) University of Twente;
Atmospheric correction; Hyperspectral; Machine learning; Radiative transfer modeling; Surface reflectance;