Downscaling Aster Land Surface Temperature over Urban Areas with Machine Learning-Based Area-To-Point Regression Kriging

Downscaling Aster Land Surface Temperature over Urban Areas with Machine Learning-Based Area-To-Point Regression Kriging

Land surface temperature (LST) is a vital physical parameter of earth surface system. Estimating high-resolution LST precisely is essential to understand heat change processes in urban environments. Existing LST products with coarse spatial resolution retrieved from satellite-based thermal infrared...

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Bibliographic Details
Main Authors: Jianhui Xu, Feifei Zhang, Hao Jiang, Hongda Hu, Kaiwen Zhong, Wenlong Jing, Ji Yang, Binghao Jia
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Remote Sensing
Subjects:
ASTER
downscaling
land surface temperature
RFATPK
Sentinel-2A
Online Access:https://www.mdpi.com/2072-4292/12/7/1082

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