Bio 

Dr. Zhenlong Li joined the Department of Geography 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. Dr. Li is named a Breakthrough Star by USC in 2020 and a Geospatial World 50 Rising Stars by the Geospatial Media and Communications in 2021. He is also a Peter and Bonnie McCausland Faculty Fellow at the USC College of Arts and Sciences (2020-2023).

He served as the 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 the Board of Director of the International Association of Chinese Professionals in Geographic Information Sciences (CPGIS). Currently, he sits on the Editorial Board of five international journals including the International Journal of Digital Earth, Geo-spatial Information Science, PLOS ONE, ISPRS International Journal of Geo-Information, and Big Earth Data. He also serves as a peer reviewer for more than 35 international journals.

 

 

Research 

Dr. Li’s primary research field is GIScience with a focus on geospatial big data, spatial computing, social media analytics, 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, human dynamics, public health, and climate change.

Dr. Li has more than 120 publications including 90 peer-reviewed journal articles, most of which have appeared in top journals in GIScience and other related fields (e.g., International Journal of Geographical Information Science, International Journal of Digital Earth, and Proceedings of National Academy of Sciences), 25 peer-reviewed articles in books and proceedings, and 4 edited books. He has received external funding support from NSF, NIH, NOAA, NASA, and Federation of Earth Science Information Partners (ESIP) among others.

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., Hodgson M., Huang X., Li X., (2022) Converting street view images to land cover maps for metric mapping: a case study on sidewalk network extraction for the wheelchair users, Computers, Environment and Urban Systems. https://doi.org/10.1016/j.compenvurbsys.2022.101808

Qiao S., Li Z., Zhang J., Sun X., Garrett C., Li X., (2022) Social capital, urbanization level, and COVID-19 vaccination uptake in the United States: A national level Analysis, Vaccines, 10(4), 625; https://doi.org/10.3390/vaccines10040625

Ning H., Li Z., Ye X., Wang S., Wang W., Huang X., (2022). Exploring the vertical dimension of street view image based on deep learning: a case study on lowest floor elevation estimation, International Journal of Geographical Information Science, 36(7). 1317-1342. https://doi.org/10.1080/13658816.2021.1981334

Zeng C., Zhang J., Li Z., Sun X., Yang X., Olatosi B., Weissman S., Li X., (2022) Population mobility and aging accelerate the outbreaks of COVID-19 in the Deep South: a county-level longitudinal analysis, Clinical Infectious Diseases, https://doi.org/10.1093/cid/ciac050

Qiao S, Li Z, Liang C, Li X, Rudisill AC. (2022) Three dimensions of COVID-19 risk perceptions and their socioeconomic correlates in the United States: A social media analysis. Risk Analysis. https://doi.org/10.1111/risa.13993

Li Z., Huang X., Hu T., Ning H., Ye X., Huang B., Li X., (2021), ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-source Multi-scale Human Mobility, Plos One, https://doi.org/10.1371/journal.pone.0255259

Li Z., Huang X., Ye X., Jiang Y., Martin Y., Ning H., Hodgson M., Li X., (2021), Measuring Global Multi-Scale Place Connectivity using Geotagged Social Media Data, Nature Scientific Reports, https://doi.org/10.1038/s41598-021-94300-7

Martín, Y., Li, Z. Ge, Y., Huang, X. (2021) Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level. Social Sciences, https://doi.org/10.3390/socsci10060227

Kupfer, J. A., Li, Z., Ning, H., & Huang, X. (2021). Using Mobile Device Data to Track the Effects of the COVID-19 Pandemic on Spatiotemporal Patterns of National Park Visitation. Sustainability, 13(16), 9366. https://doi.org/10.3390/su13169366

Jiang Y., Huang X., Li Z. (2021) Spatiotemporal patterns of human mobility and its association with land use types during COVID-19 in New York City, ISPRS International Journal of Geo-Information, https://doi.org/10.3390/ijgi10050344

Jiang Y., Li Z., Cutter S., (2021) Social Distance Integrated Gravity Model for Evacuation Destination Choice, International Journal of Digital Earth, https://doi.org/10.1080/17538947.2021.1915396

Li Z., (2020) Geospatial Big Data Handling with High Performance Computing: Current Approaches and Future Directions, In Tang, W., Wang, S., (eds.), High Performance Computing for Geospatial Applications, Springer

Li Z., Gui Z, Hofer B., Li Y., Scheider S., Shekhar S., Geospatial Information Processing Technologies, (2020) In Guo, H., Goodchild, M.F., Annoni, A. (eds.), Manual of Digital Earth, Springer

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

Li Z., Tang W., Huang Q., Shook E., Guan Q. (2020), Introduction to Big Data Computing for Geospatial Applications, ISPRS International Journal of Geo-Information, 9(8), 487; https://doi.org/10.3390/ijgi9080487

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

Jiang Y., Li Z., Ye X.,(2018), Measuring inter-city network using digital footprints from Twitter users, Proceedings of the 2nd ACM SIGSPATIAL International Workshop on PredictGIS, 11/06/2018, Seattle, Washington. https://doi.org/10.1145/3283590.3283594

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

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., https://doi.org/10.3390/ijgi5100173

Li Z., Yang C., Yu M., Liu K., Sun M.(2015) Enabling Big Geoscience Data Analytics with a Cloud-based, MapReduce-enabled and Service-oriented Workflow Framework, PloS one, 10(3), https://doi.org/10.1371/journal.pone.0116781