Lecturer, Jiangsu University China
Shen Qiu is a researcher specializing in remote sensing and geographical information systems. He earned his Ph.D. in Cartography and GIS from Beijing Normal University, preceded by a Master’s in Surveying and Mapping Engineering from China University of Geosciences and a Bachelor’s in Remote Sensing Science from Jiangsu Normal University. His research focuses on solar-induced chlorophyll fluorescence (SIF), drought monitoring, and vegetation productivity analysis. Shen has published extensively in high-impact journals, contributing to environmental monitoring and agricultural sustainability. His expertise spans machine learning applications, remote sensing data analysis, and spatial modeling for ecological assessments.
Publication Profile
Scopus
🎓 Education
Ph.D. (2018-2022): Cartography and Geographical Information System, Beijing Normal University. M.Eng. (2016-2018): Surveying and Mapping Engineering, China University of Geosciences. B.Sc. (2012-2016): Remote Sensing Science and Technology, Jiangsu Normal University
💼 Experience
Shen Qiu has conducted extensive research on remote sensing applications in environmental monitoring and precision agriculture. His work integrates machine learning, satellite data analysis, and spatial modeling to enhance drought prediction and vegetation health assessments. He has collaborated with leading institutions and researchers to develop innovative approaches for analyzing chlorophyll fluorescence and its impact on crop productivity. Shen’s contributions include advancements in downscaling techniques for remote sensing data, improving monitoring capabilities for climate change adaptation and resource management.
🏆 Awards & Honors
Recognized for multiple SCI-indexed publications in top-tier journals (JCR Q1 & Q2). Contributor to high-impact research on solar-induced chlorophyll fluorescence (SIF) and drought monitoring. Frequent presenter at international remote sensing conferences. Acknowledged for advancements in machine learning applications in remote sensing
🔍 Research Focus
Shen Qiu’s research centers on solar-induced chlorophyll fluorescence (SIF), drought monitoring, and crop yield prediction. He explores the relationship between vegetation indices, soil moisture, and primary productivity under environmental stress. His expertise includes machine learning-based remote sensing analysis, multi-source data fusion, and ecological modeling for sustainable agriculture. His studies contribute to climate resilience, precision farming, and improved environmental management strategies.
Title: Modeling of winter wheat yield prediction based on solar-induced chlorophyll fluorescence by machine learning methods
Year: 2025
Authors: Minxue Zheng, Han Hu, Yue Niu, Feng Jia, Xiaolei Geng
Citations: 0
Journal: European Journal of Remote Sensing