Papers

1

Total Citations

35

H-Index

1

About

Shifeng Li is a leading figure in atmospheric remote sensing, with a focused expertise in retrieving total precipitable water vapor (PWV) from satellite data. His most impactful work, "An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data" (2020, 35 citations), addresses a critical challenge in optical remote sensing: correcting the substantial atmospheric effects that degrade Earth surface imagery. By developing a robust algorithm for China's FY-3D satellite, Li enables more accurate radiometric transfer corrections, directly improving the quality of land and ocean observations. This contribution is vital for climate monitoring, weather prediction, and environmental studies, as water vapor is a key greenhouse gas and atmospheric variable. Li’s work bridges the gap between satellite sensor design and practical atmospheric correction, making him an essential researcher for students and professionals working with Chinese satellite data or studying atmospheric effects on remote sensing. His algorithm stands as a benchmark for operational PWV retrieval, demonstrating how precise atmospheric parameterization can unlock the full potential of space-based Earth observation.

Research Focus

Key Achievements

1
H-Index
1
Papers
35
Total Citations
35
Avg Citations/Paper
🏆 Most Cited Paper
An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data
35 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Institute of Agricultural Resources and Regional Planning

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago