Guangjian Yan

Papers

Total Citations

138

H-Index

About

Guangjian Yan is a leading figure in quantitative remote sensing, with a primary focus on atmospheric correction and land surface parameter retrieval. His work is pivotal in enhancing the accuracy of satellite-derived environmental data, particularly for thermal infrared and nighttime light observations. Yan’s most impactful contribution is the development of a modified split-window covariance-variance ratio method for retrieving atmospheric water vapor from Landsat 8 TIRS images, a foundational technique that has garnered over 120 citations and is essential for precise land surface temperature estimation. He has also advanced the understanding of aerosol impacts on nighttime light data, quantitatively analyzing how atmospheric particles distort Suomi-NPP VIIRS DNB signals over China—a critical step for reliable urban and socioeconomic monitoring. With a career marked by methodical innovation, Yan’s research directly supports applications in climate science, urban planning, and environmental monitoring. His work stands out for bridging the gap between raw satellite signals and actionable geophysical insights, making him a key resource for students and researchers tackling atmospheric correction challenges in remote sensing.