Assoc. Prof. Dr. Guanhua Zhou | Remote Sensing | Research Excellence Award
Assoc. Prof. Dr. Guanhua Zhou | Remote Sensing | Doctor at Beihang University | China
Remote Sensing expert Guanhua Zhou is an Associate Professor in the Department of Remote Sensing Science and Technology, School of Instrumentation and Optoelectronic Engineering at Beihang University, Beijing, China, where he actively contributes to teaching, research, and academic innovation in environmental observation sciences. Guanhua Zhou earned his B.S. and M.S. degrees in Geophysics from Ocean University of China and later obtained his Ph.D. in Cartography and Geographic Information Systems from the Institute of Remote Sensing Applications, Chinese Academy of Sciences, building a strong interdisciplinary academic foundation. Professionally, Guanhua Zhou has served as a visiting scholar at internationally renowned institutions including the German Aerospace Center (DLR), Karlsruhe Institute of Technology (KIT) in Germany, and Plymouth Marine Laboratory (PML) in the United Kingdom, fostering global research collaboration. His research interests include ecological and environmental remote sensing with emphasis on water quality assessment, polluted and greenhouse gas monitoring, land ecosystem simulation, big data analysis, intelligent computing in remote sensing, carbon verification, and advanced remote sensing image processing. Guanhua Zhou demonstrates strong research skills in satellite data analysis, algorithm development, environmental modeling, and data-driven intelligence. His scholarly accomplishments include over seventy academic publications, four monographs, one textbook, more than forty patents, and over ten software copyrights, reflecting notable academic recognition. In conclusion, Guanhua Zhou is a distinguished Remote Sensing scholar whose sustained research excellence and international engagement continue to advance environmental monitoring and sustainable development.
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Featured Publications
Canopy Modeling of Aquatic Vegetation: A Radiative Transfer Approach
– Remote Sensing of Environment, 2015
High-Resolution Anthropogenic Emission Inventories with Deep Learning in Northern South America
– Remote Sensing of Environment, 2025
Lithium Quantification Estimate Based on Random Forest Algorithm: A Case Study of Coipasa Salt Flats, Bolivia
– International Journal of Applied Earth Observation and Geoinformation, 2023
Deep Learning for Water Quality Multivariate Assessment in Inland Water across China
– International Journal of Applied Earth Observation and Geoinformation, 2024
Short-Time Cloud-Free Image Reconstruction Based on Time Series Images
– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023