Papers
13
Total Citations
364
H-Index
11
About
Lu She is a prominent remote sensing scientist whose research has significantly advanced our understanding of atmospheric aerosols and air quality monitoring from satellite observations. Specializing in aerosol optical depth (AOD) retrieval, dust storm detection, and satellite remote sensing, She has made substantial contributions to the field by developing innovative algorithms that bridge physical modeling and machine learning approaches. Among her most impactful contributions is her pioneering work applying deep neural networks to AOD retrieval from geostationary satellite data, including Himawari-8 and Landsat-8, demonstrating that data-driven approaches can effectively capture the complex relationships between top-of-atmosphere reflectances and aerosol properties. Her 2020 paper on Himawari-8 AOD retrieval using AERONET-trained neural networks has garnered 58 citations, reflecting its widespread adoption in the community. She has also advanced global aerosol monitoring by integrating data from four geostationary satellites — GOES-16, MSG-1, MSG-4, and Himawari-8 — to produce hourly, near-global AOD datasets. Her research extends to dust storm characterization, PM2.5 estimation, and multi-source satellite validation, collectively accumulating over 330 citations. Through combining cutting-edge machine learning with rigorous atmospheric physics, Lu She's work has meaningfully improved our capacity to monitor air pollution and aerosol dynamics from space.
Research Focus
Key Achievements
Top Papers
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- 3Dust Detection and Intensity Estimation Using Himawari-8/AHI Observation50 citations · 2018
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