Shen, Xinyi

Assistant Professor
Atmospheric and Freshwater Sciences


  • PhD, Institute of Remote Sensing and GIS, Peking University, 2012
  • BS, School of Remote Sensing and Information Engineering, Wuhan University, 2007

Research Interests

Dr. Xinyi Shen has been an Assistant Professor at the School of Freshwater Sciences at University of Wisconsin-Milwaukee since 2022. He was previously an assistant research professor at the University of Connecticut. He did postdoc work at the University of Connecticut and the University of Oklahoma. His research interests include interactions of humans, disasters, and the built environment under climate change; flood-inundation modeling and observatory using hydrological modeling and remote sensing; AI applications in natural hazards and climate change; AI applications in desert biodiversity under climate change; and remote sensing, photogrammetry and GIS.

Recent and Selected Publications

Qing Yang, Xinyi Shen*, Feifei Yang, Emmanouil Anagnostou, Kang He, Chongxun Mo, Hojjat Seyyedi, Albert J. Kettner, and Qingyuan Zhang, “Predicting Flood Property Insurance Claims over CONUS, Fusing Big Earth Observation Data”, Bulletin of American Meteorological Society, doi: 10.1175/BAMS-D-21-0082.1.

Rehenuma Lazin, Xinyi Shen*, Emmanouil Anagnostou, “Predicting flood damaged crop lands using Convolutional Neural Network (CNN)”, Environmental Research Letters, vol. 16 (5) pp. 054011 doi: 10.1088/1748-9326/abeba0.

Qing Yang, Xinyi Shen*, Emmanouil Anagnostou, Jack Eggleston, and Albert Kettner “A High-Resolution Flood Inundation Archive (2016–the Present) from Sentinel-1 SAR Imagery over CONUS”, Bulletin of the American Meteorological Society, DOI:10.1175/BAMS-D-19-0319.1.

Xinyi Shen*, Chenkai Cai#, Qing Yang#, Emmanouil Anagnostou, and Hui Li, “COVID-19 Pandemic in the Flood Season”, Science of the Total Environment, vol. 755, pp. 142634, DOI:10.1016/j.scitotenv.2020.142634.

Xinyi Shen*, Chenkai Cai, Hui Li, “Satellite reveals socioeconomic restrictions slowdown COVID-19 far more effectively than favorable weather”, Science of the Total Environment, vol. 748, pp. 141401, DOI:10.1016/j.scitotenv.2020.141401.

Rehenuma Lazin, Xinyi Shen*, and Emmanouil N. Anagnostou “Evaluation of the Hyper-Resolution Model-Derived Water Cycle Components over the Upper Blue Nile Basin”, Journal of Hydrology, DOI:10.1016/j.jhydrol.2020.125231

Xinyi Shen*, Dacheng Wang, Kebiao Mao, Emmanouil Anagnostou, and Yang Hong. (2019) “Inundation Extent Mapping by Synthetic Aperture Radar: A Review”, Remote Sensing, 11, 879, DOI: 10.3390/rs11070879, (ESI highly cited)

Xinyi Shen*, Emmanouil N. Anagnostou, George H. Allen, Robert G. Brakenridge and Albert J. Kettner (2019). “Near-Real Time Non-obstructed Inundation Mapping by Synthetic Aperture Radar”, Remote Sensing of Environment, vol. 221, 302-315. DOI: 10.1016/j.rse.2018.11.008

Xinyi Shen* and Emmanouil Anagnostou (2017) “A Framework to Improve Hyper-Resolution Hydrologic Simulation in Snow-Affected Regions”, Journal of Hydrology, vol.552, pp.1-12, DOI:10.1016/j.jhydrol.2017.05.048.

Xinyi Shen*, Yiwen Mei and Emmanouil N. Anagnostou*, (2017). “A Comprehensive Flood Events Database in Continental United States”, Bulletin of the American Meteorological Society, 98 (7), 1493-1502, DOI: 10.1175/BAMS-D-16-0125.1.

Xinyi Shen*, Emmanouil N. Anagnostou*, Yiwen Mei and Yang Hong (2016), “A Global Distributed Basin Morphometric Dataset”, Scientific Data, 4:160124, DOI: 10.1038/sdata.2016.124.

Xinyi Shen*, Humberto J. Vergara, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou*, Yang Hong, Zengchao Hao, Ke Zhang and Kebiao Mao, (2017) “GDBC: A Tool for Generating Global-Scale Distributed Basin Morphometry”, Environmental Modelling & Software, vol. 83, pp. 212–223, DOI: 10.1016/j.envsoft.2016.05.012.