Your browser doesn't support javascript.
loading
Application of a Machine Learning Algorithm in Generating an Evapotranspiration Data Product From Coupled Thermal Infrared and Microwave Satellite Observations.
Fang, Li; Zhan, Xiwu; Kalluri, Satya; Yu, Peng; Hain, Chris; Anderson, Martha; Laszlo, Istvan.
Afiliação
  • Fang L; Earth System Science Interdisciplinary Center, Cooperate Institute of Satellite Earth System Studies (CISESS), University of Maryland, College Park, MD, United States.
  • Zhan X; Center for Satellite Applications and Research (STAR), National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA), College Park, MD, United States.
  • Kalluri S; Center for Satellite Applications and Research (STAR), National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA), College Park, MD, United States.
  • Yu P; Center for Satellite Applications and Research (STAR), National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA), College Park, MD, United States.
  • Hain C; Earth System Science Interdisciplinary Center, Cooperate Institute of Satellite Earth System Studies (CISESS), University of Maryland, College Park, MD, United States.
  • Anderson M; Center for Satellite Applications and Research (STAR), National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA), College Park, MD, United States.
  • Laszlo I; Marshall Space Flight Center, National Aeronautics and Space Administration (NASA), Huntsville, AL, United States.
Front Big Data ; 5: 768676, 2022.
Article em En | MEDLINE | ID: mdl-35668815
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article