Fangni Lei

Overview

My research focuses on enhancing the quantification of global hydrological parameters and advancing the understanding of land-atmosphere interactions by integrating remote sensing big data, physical models, statistical methods, and artificial intelligence techniques. My work encompasses a range of topics, including soil moisture quantification from microwave remote sensing, land surface water-energy balance modeling, watershed-scale hydrologic modeling, hydrologic data assimilation, flood mapping, and agricultural water management. I am currently an assistant research professor at the Eversource Energy Center and the Department of Civil and Environmental Engineering at the University of Connecticut. I earned my BS, MS, and PhD degrees from Wuhan University and was a visiting student at the Hydrology and Remote Sensing Laboratory of the USDA Agricultural Research Service. Following my PhD, I continued my research as a post-doctoral associate at USDA and then as a research assistant professor at Mississippi State University.

Research Interests

Remote sensing; hydrology; agricultural water management; land-atmosphere interaction; climate change

Education

• BS, Geographic Information Systems, Wuhan University 2011
• MS, Cartography and Geographic Information Systems, Wuhan University 2013
• PhD, Cartography and Geographic Information Engineering, Wuhan University 2016

Selected Publications

• M.M. Nabi, V. Senyurek, F. Lei, M. Kurum, and A.C. Gurbuz, "Quasi-Global Assessment of Deep Learning-Based CYGNSS Soil Moisture Retrieval," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 5629–5644, 2023.
• F. Lei, V. Senyurek, M. Kurum, A. Gurbuz, D. Boyd, W.T. Crow, and R. Moorhead, "Quasi-Global Machine Learning-based Soil Moisture Estimates at High Spatio-Temporal Scales Using CYGNSS and SMAP Observations," Remote Sensing of Environment, vol. 276, p. 113041, 2022.
• J. Dong, F. Lei, and W.T. Crow, "Land transpiration-evaporation partitioning errors responsible for modeled summertime warm bias in the central United States," Nature Communications, vol. 13(1), pp. 1–8, 2022.
• F. Chen, F. Lei, K. Knipper, et al., "Application of the Vineyard Data Assimilation (VIDA) System to Vineyard Root-Zone Soil Moisture Monitoring in the California Central Valley," Irrigation Science, pp. 1–21, 2022.
• F. Lei, W.T. Crow, W.P. Kustas, J. Dong, Y. Yang, K.R. Knipper, M.C. Anderson, F. Gao, C. Nortarnicola, F. Gerifeneder, L.M. McKee, J.G. Alfieri, C.R. Hain, and N. Dokoozlian, "Data assimilation of high-resolution thermal and radar remote sensing retrievals for soil moisture monitoring in a drip-irrigated vineyard," Remote Sensing of Environment, vol. 239, p. 111622, 2020.
• V. Senyurek, F. Lei, D. Boyd, A.C. Gurbuz, M. Kurum, R. Moorhead, "Evaluations of a Machine Learning-Based CYGNSS Soil Moisture Estimates against SMAP Observations," Remote Sensing, vol. 12(21), p. 3503, 2020.
• V. Senyurek, F. Lei, D. Boyd, M. Kurum, A.C. Gurbuz, and R. Moorhead, "Machine Learning-Based CYGNSS Soil Moisture Estimates over ISMN Sites in CONUS," Remote Sensing, vol. 12(7), p. 1168, 2020.
• J. Dong, P.A. Dirmeyer, F. Lei, M.C. Anderson, T.R. Holmes, C. Hain, and W.T. Crow, "Soil Evaporation Stress Determines Soil Moisture-Evapotranspiration Coupling Strength in Land Surface Modeling," Geophysical Research Letters, vol. 47(21), 2020.
• J. Dong, W.T. Crow, R. Reichle, Q. Liu, F. Lei, and M. Cosh, "A Global Assessment of Added Value in the SMAP Level 4 Soil Moisture Product Relative to Its Baseline Land Surface Model," Geophysical Research Letters, vol. 46, pp. 6604–6613, 2019.
• H. Jiang, H. Shen, X. Li, C. Zeng, H. Liu, and F. Lei, "Extending the SMAP 9-km Soil Moisture Product Using a Spatio-Temporal Fusion Model," Remote Sensing of Environment, vol. 231, p. 111224, 2019.
• F. Lei, W.T. Crow, T.R.H. Holmes, C. Hain, and M.C. Anderson, "Global Investigation of Soil Moisture and Latent Heat Flux Coupling Strength," Water Resources Research, vol. 54(10), pp. 8196–8215, 2018.
• F. Lei, W.T. Crow, H. Shen, C.-H. Su, T.R.H. Holmes, R.M. Parinussa, and G. Wang, "Assessment of the Impact of Spatial Heterogeneity on Microwave Satellite Soil Moisture Periodic Error," Remote Sensing of Environment, vol. 205, pp. 85–99, 2018.