Papers
1
Total Citations
35
H-Index
1
About
Shuhe Zhao is a leading figure in atmospheric remote sensing, whose work has significantly advanced the retrieval of key atmospheric parameters from satellite data. His primary research focuses on the development of algorithms to correct atmospheric effects in optical imagery, with a particular emphasis on quantifying precipitable water vapor (PWV). Zhao’s most cited work, "An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data" (2020, 35 citations), addresses a critical challenge: the substantial interference of atmospheric particles on radiometric transfer from the Earth’s surface to space-based sensors. By designing a robust method to extract PWV from China’s FengYun-3D satellite, he has enabled more accurate atmospheric correction for optical remote sensing, directly improving the quality of land surface and environmental monitoring. This contribution is vital for applications ranging from climate modeling to agricultural assessment. Zhao’s work stands as a cornerstone for researchers and students seeking to understand and mitigate atmospheric distortions in satellite imagery, demonstrating how precise algorithmic innovation can unlock the full potential of Earth observation data.
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