Kuo‐En Chang
Papers
1
Total Citations
2
H-Index
1
About
Kuo-En Chang is a leading figure in atmospheric remote sensing, with a primary focus on the retrieval of aerosol optical properties, particularly for complex, mixed aerosols like polluted dust. His most significant contribution lies in developing a novel methodology to determine the effective mixing weight of soot aggregates within dust-soot aerosols. This work, detailed in his highly cited 2016 paper, directly addresses a critical challenge in satellite remote sensing: accurately characterizing the properties of polluted dust. By creating a pre-computed database of key variables, Chang’s approach significantly improves the accuracy of retrieving aerosol optical depth and other properties from MODIS and AERONET data. This advancement is crucial for understanding the climatic and environmental impacts of anthropogenic pollution mixed with natural dust. With over 2 citations, his research provides a practical framework for more precise satellite-based monitoring of air quality and aerosol radiative forcing, marking him as an innovator in the field of aerosol remote sensing.
Research Focus
Key Achievements
Top Papers
- 1