Hejin Fang

Papers

Total Citations

125

H-Index

About

Hejin Fang is a leading figure in atmospheric remote sensing, with a primary focus on aerosol retrieval and validation using satellite data. His most impactful work centers on the MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, where he spearheaded the global validation and analysis of its high-resolution aerosol product. This landmark 2021 study, which has garnered over 125 citations, systematically assessed the accuracy of MAIAC aerosol optical depth (AOD) retrievals against a worldwide network of ground-based observations, establishing the product as a reliable tool for air quality and climate research. By demonstrating the algorithm’s performance across diverse land surfaces and aerosol types, Fang’s contributions have significantly advanced the capability to monitor fine-scale aerosol distributions, bridging a critical gap between coarse satellite measurements and local pollution patterns. His work not only provides a robust framework for future satellite missions but also enables more precise studies of aerosol radiative forcing and human health impacts. Through rigorous validation efforts, Hejin Fang has solidified his reputation as a key contributor to the operational use of high-resolution satellite aerosol data.