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Department of Geography

Directory

Zhenlong Li

Title: Associate Professor
Department: Geography
College of Arts and Sciences
Email: zhenlong@sc.edu
Phone: 803-777-4590
Office: Callcott, Room 320
Resources: Curriculum Vitae [pdf]
Department of Geography
Geoinformation and Big Data Research Laboratory
Zhenlong Li

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.

Research 

Dr. Li’s primary research field is GIScience with a focus on geospatial big data analytics, high performance computing, spatiotemporal analysis/modelling, cyberGIS, and geospatial artificial intelligence (GeoAI). 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 over 50 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, International Journal of Digital Earth, and Proceedings of National Academy of Sciences. His research has been supported by the National Science Foundation, National Institute of Health, Federation of Earth Science Information Partners, and National Aeronautics and Space Administration.

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 and Recent Publications 

Ning H., Li Z., Wang C., Yang L., (2020), Choosing an appropriate training set size when using existing data to train neural networks for land cover segmentation, Annals of GIS, https://doi.org/10.1080/19475683.2020.1803402

Hu L., Li Z., Ye X., (2020) Delineating and Modelling Activity Space Using Geotagged Social Media Data, Cartography and Geographic Information Science, 47(3), 277–288 https://doi.org/10.1080/15230406.2019.1705187

Li Z., Huang Q., Emrich C., (2019) Introduction to Social Sensing and Big Data Computing for Disaster Management, International Journal of Digital Earth, 12(11), 1198–1204.

Hu F., Li Z., Yang C., Jiang Y. (2019) A graph-based approach to detect the tourist movement pattern using social media data, Cartography and Geographic Information Science, 46(4), 368–382, https://doi.org/10.1080/15230406.2018.1496036

Li Z., Huang Q., Jiang Y., Hu F. (2019), SOVAS: A Scalable Online Visual Analytic System for Big Climate Data Analysis, International Journal of Geographic Information Science, 1–22, doi: 10.1080/13658816.2019.1605073

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

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

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.

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


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