Boming Liu
Papers
3
Total Citations
72
H-Index
3
About
Boming Liu is a leading researcher in satellite remote sensing of aerosols, with a focus on advancing the accuracy and coverage of aerosol optical depth (AOD) retrievals for climate and environmental studies. His work centers on the validation, fusion, and algorithmic improvement of multi-sensor aerosol products, bridging gaps between passive and active remote sensing technologies. Liu’s major contributions include the comprehensive validation and intercomparison of MISR V23 AOD products against MODIS and AERONET observations (29 citations), which established critical benchmarks for data quality. He also pioneered the application of the GRASP algorithm to the Directional Polarimetric Camera (DPC) for high-precision AOD retrieval (24 citations), enhancing polarimetric sensor capabilities. Notably, his development of a Bayesian Maximum Entropy fusion method to combine active and passive satellite AOD data (19 citations) significantly reduced data missing ratios, enabling more robust atmospheric studies. With over 70 total citations, Liu’s work directly supports global climate change research, anthropogenic emission assessments, and biogeochemical cycle modeling. His innovative data fusion approach has been particularly impactful for regions with sparse ground-based observations, making him a key figure in advancing satellite aerosol remote sensing.
Research Focus
Key Achievements
Top Papers
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