Papers
11
Total Citations
250
H-Index
7
About
Kwon-Ho Lee is a leading expert in satellite remote sensing of atmospheric aerosols, with a focus on East Asia—a region where natural dust storms and anthropogenic pollution converge. His research centers on developing and refining algorithms to retrieve aerosol optical depth (AOD) from satellite data, enabling high-resolution monitoring of air quality over complex urban and industrial landscapes. Lee’s most cited work, “Satellite remote sensing of Asian aerosols” (2010, 105 citations), provides a foundational framework for distinguishing clean, polluted, and dust storm conditions. He has pioneered the use of machine learning and deep neural networks to estimate hourly AOD from geostationary satellites, as demonstrated in his 2021 study (35 citations), overcoming limitations of traditional physical models. His integrated neural network model for dust storm retrieval (2015, 24 citations) further advances real-time monitoring capabilities. Lee’s contributions also include validating satellite aerosol products for East Asia and characterizing long-range transported Asian dust, with studies leveraging AERONET data and backward trajectory analysis. His work directly supports air quality management in megacities like Hong Kong and the Pearl River Delta, bridging satellite observations with ground-based measurements to mitigate the impacts of regional air pollution.
Research Focus
Key Achievements
Top Papers
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- 4Retrieval of dust storm aerosols using an integrated Neural Network model24 citations · 2015
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