Bio 

Dr. Zhenlong Li joined the Department of Geography as an Assistant Professor in 2015 after receiving his Ph.D. in Earth Systems and Geoinformation Sciences from the George Mason University (GMU). He holds a B.S. (2006) in GIS from Wuhan University and an M.S. (2010) in Earth System Science from GMU. Currently, he serves on the Editorial Boards of ISPRS International Journal of Geo-Information and PLOS ONE, as Chair of the Cyberinfrastructure Specialty Group of Association of American Geographers (AAG), Co-Chair of the Cloud Computing Group of Federation of Earth Science Information Partners (ESIP), and on the Board of Directors of the International Association of Chinese Professionals in Geographic Information Sciences (CPGIS).

 

Research 

Dr. Li’s primary research field is GIScience with a focus on spatial computing, big data analytics, and geospatial cyberinfrastructure/cyberGIS. By synthesizing cutting-edge computing technologies, geospatial methods, and spatiotemporal principles, Dr. Li and his Geoinformation and Big Data Research Lab aim to accelerate spatial information extraction and advance knowledge discovery to support domain applications such as disaster management, climate analysis, human dynamics, and public health. Problems addressed, for example, include how to synthesize very large datasets in order to quickly identify the spatial relationships between two climate variables (a computational problem) and how to find spatial and temporal patterns of human activities during disasters in large datasets that are notoriously "dirty" and biased as a population sample (e.g., Twitter data). He has published 30 peer-reviewed journal articles, most of which have appeared in top journals in GIScience and other related fields such as International Journal of Geographical Information Science, Computers, Environment and Urban Systems, International Journal of Digital Earth, and Proceedings of National Academy of Sciences.

 

Teaching

• GEOG 363: Introduction to Geographic Information Systems
• GEOG 531: Quantitative Methods in Geographic Research
• GEOG 554: Spatial Programming
• GEOG 556: WebGIS
• GEOG 763: Seminar in Geographic Information Science

 

Representative Publications 

Huang X., Wang C., Li Z. (2018) A Flooding Probability Reconstruction Approach by Enhancing Near Real-time Imagery with Real-Time Gauges and Tweets, IEEE Transactions on Geoscience and Remote Sensing.

Li Z., Hodgson M., Li W., (2018) A general-purpose framework for large-scale Lidar data processing, International Journal of Digital Earth, 11(1), 26–47.

Jiang Y., Li Z., Ye X. (2018) Understanding Demographic and Socioeconomic Bias of Geotagged Twitter Users at the County Level, Cartography and Geographic Information Science. DOI: 10.1080/15230406.2018.1434834.

Wang C., Li Z., Huang X. (2018) Geospatial assessment of flooding dynamics and risks of the October ’15 South Carolina Flood, Congaree River Watershed, Southeastern Geographer (in press).

Huang X., Wang C., Li Z. (2018) A Near Real-time Flood Mapping Approach by Integrating Post-event with Satellite Imagery and Flood-related Tweets, Annals of GIS. DOI: 10.1080/19475683.2018.1450787.

Li Z., Wang C., Emrich C., Guo D., (2018) A novel approach to leveraging social media for rapid flood mapping: A case study of the 2015 South Carolina floods, Cartography and Geographic Information Science, 45(2), 97–110.

Huang Q., Li, J., Li, Z., (2017) A Hybrid Cloud Platform Based on Multi-sourced Computing and Model Resources for Geosciences, International Journal of Digital Earth, DOI: 10.1080/17538947.2017.1385652.

Li Z., Huang Q., Carbone G., Hu F. (2017), A High Performance Query Analytical Framework for Supporting Data-intensive Climate Studies, Computers, Environment and Urban Systems, 62(3), 210–221.

Yang C., Huang Q., Li Z., Liu K., & Hu F. (2017) Big Data and cloud computing: innovation opportunities and challenges, International Journal of Digital Earth 10(1),13–53.

Li Z., Yang, C., Huang, Q., Liu K., Sun, M., Xia, J., (2017). Building Model as a Service for Supporting Geosciences, Computers, Environment and Urban Systems, 61, 141–152.

Martin Y., Li Z., Cutter S., (2017) Leveraging Twitter to gauge evacuation compliance: spatiotemporal analysis of Hurricane Matthew, PLOS ONE, 12(7), e0181701.

Liu X., Huang Q., Li Z. (2017), The impact of MTUP to explore online trajectories for human mobility studies. Proceedings of the 1st ACM SIGSPATIAL International Workshop on PredictGIS.

Li, Z., Hu, F., Schnase, J. L., Duffy, D. Q., Lee, T., Bowen, M. K., & Yang, C. (2016). A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-based Climate Data with MapReduce. International Journal of Geographical Information Science, 31(1), 17–35.

Li, Z., Yang, C., Liu, K., Hu, F., & Jin, B. (2016). Automatic Scaling Hadoop in the Cloud for Efficient Process of Big Geospatial Data. ISPRS International Journal of Geo-Information, 5(10), 173–187.