Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data

Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data

The all-wave net radiation (Rn) at the land surface represents surface radiation budget and plays an important role in the Earth's energy and water cycles. Many studies have been conducted to estimate from satellite top-of-atmosphere (TOA) data using various methods, particularly the applicatio...

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Bibliographic Details
Main Authors: Shaopeng Li, Bo Jiang, Shunlin Liang, Jianghai Peng, Hui Liang, Jiakun Han, Xiuwan Yin, Yunjun Yao, Xiaotong Zhang, Jie Cheng, Xiang Zhao, Qiang Liu, Kun Jia
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:International Journal of Digital Earth
Subjects:
net radiation
energy balance
mid-low latitude
model comparison
machine learning
deep learning
modis
era5
Online Access:http://dx.doi.org/10.1080/17538947.2022.2130460

Internet

http://dx.doi.org/10.1080/17538947.2022.2130460

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