Lei Zou
  • Assistant Professor
  • Faculty Fellow, Hazard Reduction and Recovery Center
Google Scholar Profile

Biography

Dr. Lei Zou's research aims to build a sustainable future for human communities in the changing environment through spatial thinking, novel data, and intelligent algorithms. Currently, Dr. Zou serves as the PI/Co-PI for several projects funded by National Science Foundation and Texas A&M University. These projects cover five research themes:

  1. Big Geospatial Data and GeoAI for Disaster Management
  2. Urban Digital Twins for Coastal Sustainability
  3. Geospatial Approaches to Combating Health Crisis
  4. CyberGIS for Resilience Computation and Visualization
  5. GIScience for Humanities

Dr. Zou is leading the Geospatial Exploration and Resolution Research Group at TAMU (GEAR Lab) and supervising five Ph.D. students and one master's student. He serves as the vice chair of the Commission on Geospatial Analysis and Modeling of the International Cartographic Association (ICA) and the Academic Councilor for the Geographic Information Sciences & Systems (GISS) Group of the American Association of Geographers. He is a board member of the Cartography and Geographic Information Society and a member of the Research Committee, University Consortium for Geographic Information Science (UCGIS). He also serves on the editorial board of the International Journal of Digital Earth. In addition, he has been appointed as the topic editor & outreach group lead for the Big Earth Data journal.
   
The GEAR Research Group is actively recruiting undergraduate student workers, graduate students (M.S. or Ph.D.), and visiting scholars/students.

If you are interested in working with Dr. Zou on GIScience, GeoAI, Big Data, urban digital twins, disaster resilience, health GIS, and integrated social-environmental system modeling, please email at lzou@tamu.edu with your CV and a writing sample. Every self-motivated student is highly welcome to join the GEAR research group. If you have a great passion for academia, you will have the opportunity to participate in a wide range of research projects and international conferences. If you are fascinated with cutting-edge GIS and data science technologies, you will have the resources and support to train your skills, access high-performance devices, and attend technical workshops. Our goal is to help you realize your career goals through a customized tutoring plan for each student!
   
Join us, and let's do something spatial!

Courses

  • GeoDatabases
  • GIS Programming
  • GIS Practicum
  • Remote Sensing for Geographic Analysis
  • Frontiers in GIScience

 

LINKS

Research Interests

  • Geographic information science (GIScience)
  • GeoAI, Social Sensing
  • Remote Sensing
  • Digital Twins
  • Smart and Equal Resilience
  • Public Health
  • Socio-Environmental Sustainability

 

Educational Background

  • Ph.D., Environmental Sciences, Louisiana State University (Outstanding Dissertation and Dr. Joseph Martinez Memorial Awards)
  • M.S., Geographic Information Sciences, Chinese Academy of Sciences
  • B.E., Remote Sensing, Wuhan University

Awards & Honors

  • 2022 Global Young Scientist Award, World GIS Developers Conference (WGDC) 2022
  • 2021 Best Paper Award, International Symposium on Geospatial Approaches to Combating Covid-19
  • 2021 ICA Scholarship Award, 30th International Cartographic Conference
  • 2019 ICA Scholarship Award, 29th International Cartographic Conference
  • 2018 Outstanding Student Dissertation Award, College of Coast & Environment, Louisiana State University
  • 2018 Dr. Joseph Martinez Memorial Award, College of Coast & Environment, Louisiana State University
  • 2018 Dr. Joseph Martinez Memorial Award, College of Coast & Environment, Louisiana State University

  • 2016 Graduate Dean's Summer Research Award, Louisiana State University

Selected Publications

    • Lam, N.S.N., Cai, H. and Zou, L., 2022. Editorial for the Special Issue: “Human-Environment Interactions Research Using Remote Sensing.” Remote Sensing, 14(11), p.2720.
    • *Zhou, B., Zou, L., Mostafavi, A., *Lin, B., *Yang, M., Gharaibeh, N., Cai, H., *Abedin, J. and *Mandal, D., 2022. VictimFinder: Harvesting rescue requests in disaster response from social media with BERT. Computers, Environment and Urban Systems, 95, p.101824.
    • *Lin, B., Zou, L., Duffield, N., Mostafavi, A., Cai, H., *Zhou, B., Tao, J., *Yang, M., *Mandal, D. and *Abedin, J., 2022. Revealing the linguistic and geographical disparities of public awareness to Covid-19 outbreak through social media. International Journal of Digital Earth, 15(1), pp.868-889.
    • *Yang, M., Zou, L., Cai, H., Qiang, Y., *Lin, B., *Zhou, B., *Abedin, J. and *Mandal, D., 2022. Spatial-temporal land loss modeling and simulation in a vulnerable coast: A case study in coastal Louisiana. Remote Sensing, 14(4), p.896.
    • Cai, H., Lam, N.S. and Zou, L., 2022. Incorporating neighborhood scale effects into land loss modeling using semivariograms. Journal of Geographical Systems, pp.1-21.
    • Ren, M., Park, S., Xu, Y., Huang, X., Zou, L., Wong, M.S. and Koh, S.Y., 2022. Impact of the COVID-19 pandemic on travel behavior: A case study of domestic inbound travelers in Jeju, Korea. Tourism Management, 92, p.104533.
    • Zhang, Z., Zou, L., Li, W., Usery, L., Albrecht, J. and Armstrong, M., 2021. Cyberinfrastructure and intelligent spatial decision support systems. Transactions in GIS, 25(4), pp.1651-1653.
    • Yang, B., Wang, Z., Zou, L., Zou, L. and Zhang, H., 2021. Exploring the eco-efficiency of cultivated land utilization and its influencing factors in China's Yangtze River Economic Belt, 2001–2018. Journal of Environmental Management, 294, p.112939.
    • Wang, K., Lam, N.S., Zou, L. and Mihunov, V., 2021. Twitter use in hurricane Isaac and its implications for disaster resilience. ISPRS International Journal of Geo-Information, 10(3), p.116.
    • Huang, X., Zhu, D., Zhang, F., Liu, T., Li, X. and Zou, L., 2021. Sensing population distribution from satellite imagery via deep learning: Model selection, neighboring effects, and systematic biases. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, pp.5137-5151.
    • Mihunov, V.V., Lam, N.S., Zou, L., Wang, Z. and Wang, K., 2020. Use of Twitter in disaster rescue: lessons learned from Hurricane Harvey. International Journal of Digital Earth, 13(12), pp.1454-1466.
    • Correll, R.M., Lam, N.S., Mihunov, V.V., Zou, L. and Cai, H., 2021. Economics over risk: Flooding is not the only driving factor of migration considerations on a vulnerable coast. Annals of the American Association of Geographers, 111(1), pp.300-315.
    • Zou, L., Lam, N.S., Shams, S., Cai, H., Meyer, M.A., Yang, S., Lee, K., Park, S.J. and Reams, M.A., 2019. Social and geographical disparities in Twitter use during Hurricane Harvey. International Journal of Digital Earth, 12(11), pp.1300-1318.
    • Bushra, N., Rohli, R.V., Lam, N.S., Zou, L., Mostafiz, R.B. and Mihunov, V., 2019. The relationship between the normalized difference vegetation index and drought indices in the South Central United States. Natural Hazards, 96(2), pp.791-808.
    • Kirby, R.H., Reams, M.A., Lam, N.S., Zou, L., Dekker, G.G. and Fundter, D.Q.P., 2019. Assessing social vulnerability to flood hazards in the Dutch Province of Zeeland. International Journal of Disaster Risk Science, 10(2), pp.233-243.
    • Li, R., Crowe, J., Leifer, D., Zou, L. and Schoof, J., 2019. Beyond big data: Social media challenges and opportunities for understanding social perception of energy. Energy Research & Social Science, 56, p.101217.
    • Mihunov, V.V., Lam, N.S., Rohli, R.V. and Zou, L., 2019. Emerging disparities in community resilience to drought hazard in south-central United States. International Journal of Disaster Risk Reduction, 41, p.101302.
    • Zhang, B., Chen, Z., Peng, D., Benediktsson, J.A., Liu, B., Zou, L., Li, J. and Plaza, A., 2019. Remotely sensed big data: Evolution in model development for information extraction [point of view]. Proceedings of the IEEE, 107(12), pp.2294-2301.
    • Zou, L., Lam, N.S., Cai, H. and Qiang, Y., 2018. Mining Twitter data for improved understanding of disaster resilience. Annals of the American Association of Geographers, 108(5), pp.1422-1441.
    • Cai, H., Lam, N.S., Zou, L. and Qiang, Y., 2018. Modeling the dynamics of community resilience to coastal hazards using a Bayesian network. Annals of the American Association of Geographers, 108(5), pp.1260-1279.
    • Lam, N.S.N., Cheng, W., Zou, L. and Cai, H., 2018. Effects of landscape fragmentation on land loss. Remote sensing of environment, 209, pp.253-262.
    • Mihunov, V.V., Lam, N.S., Zou, L., Rohli, R.V., Bushra, N., Reams, M.A. and Argote, J.E., 2018. Community resilience to drought hazard in the south-central United States. Annals of the American Association of Geographers, 108(3), pp.739-755.
    • Cai, H., Lam, N.S., Qiang, Y., Zou, L., Correll, R.M. and Mihunov, V., 2018. A synthesis of disaster resilience measurement methods and indices. International journal of disaster risk reduction, 31, pp.844-855.
    • Lam, N.S.N., Qiang, Y., Li, K., Cai, H. and Zou, L., 2018. Extending resilience assessment to dynamic system modeling: perspectives on human dynamics and climate change research. Journal of Coastal Research, (85 (10085)), pp.1401-1405.
    • Lam, N.S.N., Xu, Y.J., Liu, K.B., Dismukes, D.E., Reams, M., Pace, R.K., Qiang, Y., Narra, S., Li, K., Bianchette, T.A., Cai, H., Zou, L. and Mihunov, V. 2018. Understanding the Mississippi River Delta as a coupled natural-human system: Research methods, challenges, and prospects. Water, 10(8), p.1054.
    • Qiang, Y., Lam, N.S., Cai, H. and Zou, L., 2017. Changes in exposure to flood hazards in the United States. Annals of the American Association of Geographers, 107(6), pp.1332-1350.
    • Cai, H., Lam, N.S.N., Zou, L., Qiang, Y. and Li, K., 2016. Assessing community resilience to coastal hazards in the Lower Mississippi River Basin. Water, 8(2), p.46.
    • Rohli, R.V., Bushra, N., Lam, N.S., Zou, L., Mihunov, V., Reams, M.A. and Argote, J.E., 2016. Drought indices as drought predictors in the south-central USA. Natural Hazards, 83(3), pp.1567-1582.
    • Shen, Q., Li, J.S., Zhang, B., Wu, Y.H., Zou, L. and Wu, T.X., 2016. Analyzing Spectral Characteristics of Water Involving In-Situ Multiangle Polarized Reflectance and Extraction of Water-Leaving Radiance. Spectroscopy and Spectral Analysis, 36(10), pp.3269-3273.
    • Zou, L., Kent, J., Lam, N.S.N., Cai, H., Qiang, Y. and Li, K., 2015. Evaluating land subsidence rates and their implications for land loss in the lower Mississippi River basin. Water, 8(1), p.10.
    • Li, K., Lam, N.S., Qiang, Y., Zou, L. and Cai, H., 2015. A cyberinfrastructure for community resilience assessment and visualization. Cartography and Geographic Information Science, 42(sup1), pp.34-39.
    • Zhang, F., Zhang, B., Li, J., Shen, Q., Wu, Y., Wang, G., Zou, L. and Wang, S., 2014. Validation of a synthetic chlorophyll index for remote estimates of chlorophyll-a in a turbid hypereutrophic lake. International Journal of Remote Sensing, 35(1), pp.289-305.
    • Zou, L., *Zhou, B., *Lin, B., *Mandal, D., Cai, H., *Yang, M., *Abedin, J. 2022. Empowering disaster response with social media and GeoAI: Opportunities and Challenges. AutoCarto 2022.
    • *Zhou, B., Zou, L., *Yang, M., *Lin, B., *Mandal, D. 2022. Overlooked Voices under Strict Lockdown: Mapping Humanitarian Needs in 2022 Shanghai COVID-19 Outbreak. AutoCarto 2022.
    • *Lin, B., Zou, L., *Yang, M., *Zhou, B. 2022. Multi-granular geovisualizations of public perceptions of COVID-19 through the lens of Twitter. AutoCarto 2022.
    • *Mandal, D., Zou, L., Cai, H., *Lin, B., *Zhou, B., *Abedin, J., *Yang, M. 2022. Uncertainties in geolocating social media data for disaster management. AutoCarto 2022.
    • Zou, L., 2021. Mapping the disparities of community resilience to natural hazards in the United States. Abstracts of the ICA, 3, p.330.
    • Zou, L., 2019. Visualizing and mining social media data for smart emergency management. Abstracts of the ICA, 1, p.442.
    • Lam, N.S.N., Cai, H., Zou, L. and Liu, K.B., 2019. Scale effects on land loss modeling in the Mississippi River Delta. Abstracts of the ICA, 1, p.205.
    • *Chen, X., Zou, L. and Zhao, B., 2019. Detecting climate change deniers on Twitter using a deep neural network. Proceedings of the 2019 11th International Conference on Machine Learning and Computing (pp. 204-210).
    • Zou, L., Zhang, B., Li, J., Shen, Q., Zhang, F. and Wang, G., 2014. A study on retrieval algorithm of black water aggregation in Taihu Lake based on HJ-1 satellite images. IOP Conference Series: Earth and Environmental Science (Vol. 17, No. 1, p. 012100). IOP Publishing.
    • Zou, L., Zhang, B., Li, J., Song, Y., Shen, Q. and Li, L., 2012. A comparative analysis of the ‘transmittance’ method between using integrating sphere and filter holders for measuring light absorption by aquatic particles. 2012 IEEE International Geoscience and Remote Sensing Symposium (pp. 2567-2570). Ieee.
    • Li, J., Zhang, B., Shen, Q., Zou, L. and Li, L., 2012. Monitoring water quality of Lake Taihu from HJ-CCD data using empirical models. 2012 IEEE International Geoscience and Remote Sensing Symposium (pp. 812-815). Ieee.
    • Lam, N.S.N., Xu, Y.J., Pace, R.K., Liu, K.B., Qiang, Y., Narra, S., Bianchette, T.A., Cai, H., Zou, L., Li, K. and Joshi, S., 2019. Collaboration across boundaries: Reflections on studying the sustainability of the Mississippi River Delta as a coupled natural-human system. In Collaboration Across Boundaries for Social-Ecological Systems Science (pp. 361-393). Palgrave Macmillan, Cham.
    • Zou, L., Lam, N.S.N., Cai, H., 2019. A framework for analyzing and visualizing Twitter use patterns during natural hazards. US National Report for the International Cartographic Association.
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