Xun Liang

Papers

Total Citations

125

H-Index

About

Xun Liang is a leading figure in atmospheric remote sensing, whose research focuses on the development, validation, and application of satellite-based aerosol products. His most impactful work centers on the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, a high-resolution approach that has revolutionized the study of air quality and climate. Liang’s landmark 2021 study, which provides a global validation and analysis of the MODIS MAIAC aerosol product, has garnered over 125 citations, cementing its role as a foundational reference for researchers worldwide. This work not only demonstrated the product’s accuracy across diverse environments but also enabled more precise tracking of particulate matter, with direct implications for public health and environmental policy. Beyond this, Liang’s contributions extend to improving aerosol retrieval methods, advancing our understanding of aerosol-cloud interactions, and supporting the next generation of Earth-observing missions. His rigorous validation frameworks and open-data approaches have made his research indispensable for both climate modelers and atmospheric scientists, establishing him as a key architect in the effort to monitor and mitigate the impacts of aerosols on our planet.