Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland Article

Zhang, Caiyun, Brodylo, David, Rahman, Mizanur et al. (2022). Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland . SCIENCE OF THE TOTAL ENVIRONMENT, 831 10.1016/j.scitotenv.2022.154969

cited authors

  • Zhang, Caiyun; Brodylo, David; Rahman, Mizanur; Rahman, Md Atiqur; Douglas, Thomas A; Comas, Xavier

authors

publication date

  • July 20, 2022

published in

keywords

  • ALGORITHM
  • Environmental Sciences
  • Environmental Sciences & Ecology
  • Everglades
  • FLUXNET
  • Life Sciences & Biomedicine
  • MODIS
  • Machine learning ensemble
  • PRODUCTS
  • QUANTIFICATION
  • SITES
  • Science & Technology
  • VEGETATION
  • Wetland ET upscaling
  • Wetland evapotranspiration estimation

Digital Object Identifier (DOI)

publisher

  • ELSEVIER

volume

  • 831