About

Shuaiyi Shi is a leading researcher in satellite-based aerosol remote sensing, with a focus on improving the retrieval of aerosol optical depth (AOD) and understanding biomass burning aerosols. Their work has garnered over 150 citations, reflecting its significance in atmospheric science. Shi’s major contributions include developing innovative multisensor data synergy methods that integrate observations from MODIS, AATSR, VIIRS, and geostationary satellites like Himawari-8 to enhance AOD retrieval accuracy over complex land surfaces. Notably, their 2019 study on biomass burning aerosol characteristics, using 18 years of AERONET data across seven global sites, has been cited 59 times and provides critical insights into aerosol aging and vegetation-type impacts. Shi also pioneered the N-Dimensional Cost Function method for multitemporal AOD retrieval from geostationary data, advancing real-time air quality monitoring. More recently, their improved aerosol retrieval algorithm for China’s FY-3D/MERSI-II sensor demonstrates ongoing innovation in satellite remote sensing. With achievements spanning algorithm development, validation studies, and global aerosol characterization, Shi’s work directly supports climate modeling, environmental monitoring, and public health research, making them a key figure in advancing our understanding of atmospheric aerosols.

Research Focus

Key Achievements

6
H-Index
7
Papers
149
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Biomass burning aerosol characteristics for different vegetation types in different aging periods
59 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 32
🏛 Institutions: State Key Laboratory of Remote Sensing Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago