MODIS-Based Estimation of Terrestrial Latent Heat Flux over North America Using Three Machine Learning Algorithms

MODIS-Based Estimation of Terrestrial Latent Heat Flux over North America Using Three Machine Learning Algorithms

Terrestrial latent heat flux (LE) is a key component of the global terrestrial water, energy, and carbon exchanges. Accurate estimation of LE from moderate resolution imaging spectroradiometer (MODIS) data remains a major challenge. In this study, we estimated the daily LE for different plant functi...

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Bibliographic Details
Main Authors: Xuanyu Wang, Yunjun Yao, Shaohua Zhao, Kun Jia, Xiaotong Zhang, Yuhu Zhang, Lilin Zhang, Jia Xu, Xiaowei Chen
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Remote Sensing
Subjects:
latent heat
machine learning algorithms
plant functional type
Online Access:https://www.mdpi.com/2072-4292/9/12/1326

Internet

https://www.mdpi.com/2072-4292/9/12/1326

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