Shanlong Wu
Papers
2
Total Citations
25
H-Index
2
About
Shanlong Wu is a leading researcher in the field of satellite remote sensing, specializing in atmospheric correction and aerosol retrieval for moderate to high spatial resolution (MHSR) optical imagery. His work directly addresses the critical challenge of extracting accurate land surface information from satellite data in complex environments, particularly in arid and urban areas. Wu’s most influential contribution, "An Improved Aerosol Optical Depth Retrieval Algorithm for Moderate to High Spatial Resolution Optical Remotely Sensed Imagery" (2017, 19 citations), provides a robust method for monitoring air pollution at city scales by accurately deriving aerosol optical depth (AOD) from 30-meter resolution imagery. He further advanced the field with "An Atmospheric Correction Method over Bright and Stable Surfaces" (2020, 6 citations), solving the persistent problem of AOD retrieval over bright surfaces like deserts and bare ground—a key hurdle for environmental monitoring in dry regions. These innovations are essential for applications ranging from urban air quality assessment to climate modeling. Wu’s work is foundational for researchers and practitioners seeking to unlock the full potential of high-resolution satellite data for Earth observation.
Research Focus
Key Achievements
Top Papers
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