Shuai Yin

Papers

Total Citations

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About

Shuai Yin is a leading researcher in satellite-based atmospheric remote sensing, with a primary focus on aerosol optical depth (AOD) retrieval over land. His work is instrumental in improving the accuracy of greenhouse gas monitoring by addressing the critical challenge of cloud and aerosol interference. Yin’s major contributions include the development of two pioneering algorithms for the GOSAT TANSO-CAI sensor: a Modified Aerosol Free Vegetation Index (MAFVI) algorithm and a Dark Target (DT) algorithm. These methods enable precise AOD retrieval from multi-band satellite data, directly enhancing the detection and correction of atmospheric disturbances in greenhouse gas observations. His most cited papers, including "A Modified Aerosol Free Vegetation Index Algorithm..." (2016, 6 citations) and "A Dark Target Algorithm..." (2017, 5 citations), have laid the groundwork for more reliable satellite-derived environmental data. By refining the way we measure aerosols over land, Yin’s research supports critical applications in climate modeling, air quality monitoring, and carbon cycle studies. His work represents a vital step forward in the accurate quantification of Earth’s atmospheric composition, making him a key contributor to the field of satellite remote sensing.