Papers
2
Total Citations
36
H-Index
2
About
Dr. Yulong Fan is a leading researcher in satellite-based aerosol remote sensing, whose work is transforming how we monitor atmospheric aerosols on a global scale. His primary research areas focus on developing advanced retrieval algorithms for aerosol optical depth (AOD) using both polar-orbiting and geostationary satellite data. Dr. Fan’s major contributions include pioneering the use of data-driven methods, such as fully connected neural networks (FCNN), to overcome the limitations of traditional, computationally expensive radiative transfer models. His innovative "SREMARA" algorithm, which combines simplified aerosol retrieval with robust surface reflectance estimation, enables rapid and accurate AOD retrieval from satellites like GOCI-II. The impact of his work is evident in his highly cited publications, including his 2023 paper on FCNN-based retrieval (25 citations) and his validation study of GOCI-II hourly AOD data (11 citations). Notably, Dr. Fan’s research addresses the critical challenge of dynamic regional aerosol monitoring, leveraging the high-frequency observation capabilities of geostationary satellites to provide near-real-time insights into air quality and climate processes. His work is essential for advancing our understanding of aerosol transport and its environmental impacts.
Research Focus
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