Papers

4

Total Citations

176

H-Index

2

About

Quanliang Chen’s research bridges atmospheric remote sensing and materials science, with a primary focus on retrieving and validating key atmospheric parameters over China. His most impactful work, an evaluation of precipitable water vapor from radiosonde, MODIS, and AERONET against GPS measurements (148 citations), established a critical benchmark for satellite-based water vapor retrieval accuracy. Chen further characterized China’s cloud optical depth climatology using 14 years of MODIS data, revealing spatial and temporal patterns essential for climate modeling. In aerosol science, he rigorously assessed SKYNET’s performance against AERONET over Beijing, demonstrating near-perfect correlation coefficients (>0.994) for aerosol optical depth retrieval. Demonstrating remarkable versatility, Chen recently ventured into materials science with a 2024 study on precise photochemical post-processing of molecular crystals, exploring their potential as flexible smart materials for optics and electronics. This cross-disciplinary leap—from satellite validation to crystal engineering—showcases Chen’s ability to tackle fundamental measurement challenges across vastly different scales, from atmospheric columns to molecular lattices.

Research Focus

Key Achievements

2
H-Index
4
Papers
176
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
Evaluation of radiosonde, MODIS-NIR-Clear, and AERONET precipitable water vapor using IGS ground-based GPS measurements over China
148 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 26
🏛 Institutions: Chengdu University of Information Technology, Jilin University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago