Publications

Articles in Peer-reviewed Journals

2022

Huang X., Wang S., Zhang M., Hu T., Hohl A., She B., Gong X., Li J., Liu X., Gruebner O.,Liu R., L X., Liu Z., Ye X., Li Z., (2022), Social media mining under the COVID-19 context: progress, challenges, and opportunities, International Journal of Applied Earth Observation and Geoinformation (in press)

Ozigbu, C. E., Olatosi, B., Li, Z., Hardin, J. W., & Hair, N. L. (2022). Correlates of Zero-Dose Vaccination Status among Children Aged 12–59 Months in Sub-Saharan Africa: A Multilevel Analysis of Individual and Contextual Factors. Vaccines, 10(7), 1052. https://doi.org/10.3390/vaccines10071052 

Huang X., Zhao B., Li Z, Bao S., Zhang S. (2022) Black businesses matter: A longitudinal study of black owned restaurants in the COVID-19 pandemic. Annals of the American Association of Geographers. https://dx.doi.org/10.1080/24694452.2022.2095971 

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

Wang S., Zhang M., Huang X., Hu T., Li Z., Sun Q., Liu Y. (2022). Urban-regional disparities in mental health signals in Australia during the COVID-19 pandemic: a study via Twitter data and machine learning models, Cambridge Journal of Regions, Economy and Society. https://doi.org/10.1093/cjres/rsac025

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

Kazemi M., Weng Q., Haghi V., Li Z., Arsanjani J., (2022). Learning-based methods for detection and monitoring of shallow flood-affected areas: Impact of shallow-flood spreading on vegetation density, Canadian Journal of Remote Sensing, https://doi.org/10.1080/07038992.2022.2072277

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

Kazemi-Garajeh M., Blaschke T., Haghi V., Weng Q., Kamran K., Li Z., (2022). A comparison between Sentinel-2 and Landsat 8 OLI satellite images for soil salinity distribution mapping using a deep learning convolutional neural network, Canadian Journal of Remote Sensing. https://doi.org/10.1080/07038992.2022.2056435

Zhang, M., Wang, S., Hu, T., Fu, X., Wang, X., Hu, Y., Halloran B., Li Z., Cui Y., Liu H., Liu Z., Bao, S. (2022). Human mobility and COVID-19 transmission: a systematic review and future directions, Annals of GIS, https://doi.org/10.1080/19475683.2022.2041725

Huang X., Xu Y., Liu R., Wang S., Wang S., Zhang M., Kang Y. Zhang Z., Gao S., Li Z., Hu T.  Exploring the spatial disparity of home-dwelling time patterns in the U.S. during the COVID-19 pandemic via Bayesian inference, Transactions in GIS, https://doi.org/10.1111/tgis.12918

Yang Y., Zhang L., Wu L., Li Z., Does distance still matter? Moderating effects of distance measures on the relationship between pandemic severity and bilateral tourism demand, Journal of Travel Research, https://doi.org/10.1177/00472875221077978

Zhang J., Olatosi B., Yang X., Weissman S., Li Z., Hu J., Li X., (2022) Studying patterns and predictors of HIV viral suppression using A Big Data approach: A research protocol, BMC Infectious Diseases, (2022) 22:122, https://doi.org/10.1186/s12879-022-07047-5

Morgan G., Wang C., Li Z., Schill S., Morgan D., Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection: A Comparative Study, ISPRS International Journal of Geo-Information, https://doi.org/10.3390/ijgi11020100

Wang S., Huang X., Hu T., Zhang M., Li Z., Ning H., Corcoran J., Khan A., Liu Y., Zhang J., Li X., (2022), The times, they are a-changin’: tracking the shifts in mental health signals in Australia from the early to later phase of the COVID-19 pandemic, BMJ Global Health, 7(1), http://dx.doi.org/10.1136/bmjgh-2021-007081

Song, Y., Ning, H., Ye, X., Chandana, D., & Wang, S. (2022). Analyze the usage of urban greenways through social media images and computer visionEnvironment and Planning B: Urban Analytics and City Science, 23998083211064624.

Huang X., Martin Y., Wang S., Zhang M., Gong X., Ge Y., Li Z. (2022)  The promise of excess mobility analysis: measuring episodic-mobility with geotagged social media data, Cartography and Geographic Information Science, https://doi.org/10.1080/15230406.2021.2023366

Li, X., Ning, H., Huang, X., Dadashova, B., Kang, Y., & Ma, A. (2022). Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images. Cartography and Geographic Information Science, 49(1), 32-49.

2021

Ning H., Li Z., Ye X., Wang S., Wang W., Huang X., (2021). 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, 1-26.  https://doi.org/10.1080/13658816.2021.1981334

Lyu T., Hair N., Yell N., Li Z., Qiao S., Liang C., Li X., (2021). Temporal Geospatial Analysis of COVID-19 Pre-infection Determinants of Risk in South Carolina, International Journal of Environmental Research and Public Health,18(18), 9673. https://doi.org/10.3390/ijerph18189673

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 VisitationSustainability13(16), 9366. https://doi.org/10.3390/su13169366

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, 16(8): e0255259. https://doi.org/10.1371/journal.pone.0255259

Hu T., Wang S., She B., Zhang M., Huang X., Cui Y., …, Li Z., (2021) Human Mobility Data in the COVID-19 Pandemic: Characteristics, Applications, and Challenges, International Journal of Digital Earth, https://doi.org/10.1080/17538947.2021.1952324

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, Scientific Reports, https://doi.org/10.1038/s41598-021-94300-7

Hu, T., Wang, S., Luo, W., Yan, Y., Zhang, M., Huang, X., … & Li, Z. (2021). Revealing public opinion towards COVID-19 vaccines using Twitter data in the United States: a spatiotemporal perspective, Journal of Medical Internet Research, https://doi.org/10.2196/30854

Jiang, Y., Guo, D., Li, Z. Hodgson, M., (2021) A novel big data approach to measure and visualize urban accessibility. Computational Urban Science. 1, 10 (2021). https://doi.org/10.1007/s43762-021-00010-1 

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

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

Zeng C., Zhang J., Li Z., Sun X., Olatosi B., Weissman S., Li X., (2021) Spatial-temporal relationship between population mobility and COVID-19 outbreaks in South Carolina: A time series forecasting analysis, Journal of Medical Internet Research, https://doi.org/10.2196/27045

Li Z., Qiao S., Jiang Y., Li X., (2021), Building a Social media-based HIV Risk Behavior Index to Inform the Prediction of HIV New Diagnosis: A Feasibility Study, AIDS , https://doi.org/10.1097/qad.0000000000002787

Ye X., Wang W., Zhang X., Li Z., Yu D., Du J., Chen Z., (2021), Reconstructing spatial information diffusion networks with heterogeneous agents and text contents, Transactions in GIS, https://doi.org/10.1111/tgis.12747

Zeng C., Zhang J., Sun X., Li Z., Weissman S., Olatosi B.,  Li X., (2021), County-level predictors of retention in care status among people living with HIV in South Carolina from 2010 to 2016: A data-driven approach, AIDS, https://doi.org/10.1097/qad.0000000000002832

Huang X., Li Z., Jiang Y., Ye X., Deng C., Zhang J., Li X., (2021), The characteristics of multi-source mobility datasets and how they reveal the luxury nature of social distancing in the U.S., International Journal of Digital Earth, https://doi.org/10.1080/17538947.2021.1886358

Xu D., Huang X., Mango J., Li X., Li Z., (2021), Simulating multi-exit evacuation using deep reinforcement learning, Transactions in GIS, https://doi.org/10.1111/tgis.12738

Qiao S., Li Z., Weissman S., Li X., Olatosi B., Davis C., Mansaray A., (2021), Disparity in HIV service interruption in the outbreak of COVID-19: A mixed-method study in South Carolina, AIDS and Behavior, 25: 49-57 https://doi.org/10.1007/s10461-020-03013-x

2020

Li Z., Li X., Porter D., Zhang J., Jiang Y., Olatosi B., Weissman S. (2020)  Monitoring the Spatial Spread of COVID-19 and Effectiveness of Control Measures Through Human Movement Data: Proposal for a Predictive Model Using Big Data Analytics, JMIR Research Protocols, https://doi.org/10.2196/24432

Huang X., Li Z., Lu J., Wang S., Wei H., Chen B.  (2020) Time-series clustering for home dwell time during COVID-19: what can we learn from it?, ISPRS International Journal of Geo-Information, https://doi.org/10.3390/ijgi9110675

Huang X., Li Z., Jiang Y., Li X., Porter D. (2020) Twitter reveals human mobility dynamics during the COVID-19 pandemic, PloS One, https://doi.org/10.1371/journal.pone.0241957

Yang C., Sha D., Liu S., Li Y., Lan H., Guan W., Hu T., Li Z., Zhang Z., Thompson J., Wang Z., Wong D., Ruan  S., Yu M., Richardson D., et al. (2020) Taking the pulse of COVID-19: A spatiotemporal perspective, International Journal of Digital Earth, https://doi.org/10.1080/17538947.2020.1809723

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 segmentationAnnals 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

Huang X., Wang C., Li Z., Ning H., Kim H., (2020), A 100m population grid in the CONUS by disaggregating census data with open-source Microsoft building footprints, Big Earth Data, https://doi.org/10.1080/20964471.2020.1776200

Yu M., Bambacus G., Cervone G., Clarke K., Huang Q., Li J., Li W., Li Z., Liu Q., Yang J., Yang, C., (2020), Spatiotemporal Event Detection: A Review, International Journal of Digital Earth, https://doi.org/10.1080/17538947.2020.1738569

Xu D., Huang X., Li Z., Li X. (2020), Local Motion Simulation using Deep Reinforcement Learning, Transactions in GIS, https://doi.org/10.1111/TGIS.12620

Ning H., Li Z., Hodgson M., Wang C., (2020), Prototyping a Social Media Flooding Photo Screening System Based on Deep Learning, ISPRS International Journal of Geo-Information, 9(2), 104; https://doi.org/10.3390/ijgi9020104

Martín Y., Cutter S.L. Li Z, Emrich C., Mitchell, J.T. (2020) Using geotagged tweets to track population movements to and from Puerto Rico after Hurricane Maria. Population and Environment , https://doi.org/10.1007/s11111-020-00338-6

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

Ning H., Huang X., Li Z., Wang C., Xiang D., (2020) Detecting New Building Construction in Urban Areas Based on Images of Small Unmanned Aerial System, Papers in Applied Geography, https://doi.org/10.1080/23754931.2019.1707108

Pham E., Emrich C., Li Z., Mitchem J., Cutter S., (2020) Evacuation Departure Timing during Hurricane Matthew, Weather, Climate, and Society, https://doi.org/10.1175/WCAS-D-19-0030.1

Huang X., Li Z., Wang C., Ning H., (2020),  Identifying disaster related social media for rapid response: a visual-textual fused CNN architecture, International Journal of Digital Earth, 13(9), https://doi.org/10.1080/17538947.2019.1633425

Li Z., Huang Q., Jiang Y., Hu F. (2020) , SOVAS: A Scalable Online Visual Analytic System for Big Climate Data Analysis, International Journal of Geographic Information Science, 34(6) https://doi.org/10.1080/13658816.2019.1605073

Martín Y., Cutter S., Li Z.,(2020) Bridging social media and survey data for the evacuation assessment of hurricanes, Natural Hazard Review, 21(2), https://doi.org/0.1061/(ASCE)NH.1527-6996.0000354  

2019

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), https://doi.org/10.1080/17538947.2019.1670951

Jiang Y., Li Z., Cutter S.,(2019) Social network, activity space, sentiment, and evacuation: what can social media tell us? Annals of the American Association of Geographers, 109(6), https://doi.org/10.1080/24694452.2019.1592660

Dahal, Kumar, Li Z.,(2019) Spatiotemporal Topic Modeling and Sentiment Analysis of Global Climate Change Tweets, Social Network Analysis and Mining, 24(9)  https://doi.org/10.1007/s13278-019-0568-8

Yang L., Sun X., Li Z. (2019)  An Efficient Framework for Remote Sensing Parallel Processing: Integrating the Artificial Bee Colony Algorithm and Multiagent Technology, Remote Sensing, 11(2), https://doi.org/10.3390/rs11020152

Huang X., Wang C. Li Z. Ning H.,(2019) A visual-textual fused approach to automated tagging of flood-related tweets during a flood eventInternational Journal of Digital Earth, 12(11), https://doi.org/10.1080/17538947.2018.1523956

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), https://doi.org/10.1080/15230406.2018.1496036

Jiang Y., Li Z., Ye X. (2019) Understanding Demographic and Socioeconomic Bias of Geotagged Twitter Users at the County Level, Cartography and Geographic Information Science, 46(3), https://doi.org/10.1080/15230406.2018.1434834

2018

Deng, C., Lin, W., Ye, X., Li, Z., Zhang, Z., Xu, G. (2018) Social media data as a proxy for hourly fine-scale electric power consumption estimation. Envrionment and Planning A: Economy and Space, 50(8) https://doi.org/10.1177/0308518X18786250

Huang X., Wang C.,  Li Z. (2018) A Flooding Probability Reconstruction Approach by Enhancing Near Real-Time Imagery with Real-Time Gauges and TweetsIEEE Transactions on Geoscience and Remote Sensing, 56(8), https://doi.org/10.1109/TGRS.2018.2835306

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, 58(2), 164-180, https://doi.org/10.1353/sgo.2018.0020

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, 24(2), https://doi.org/10.1080/19475683.2018.1450787

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, https://doi.org/10.1080/17538947.2016.1269842

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), https://doi.org/10.1080/15230406.2016.1271356

Huang Q., Li, J., Li, Z., (2018) A Hybrid Cloud Platform Based on Multi-sourced Computing and Model Resources for Geosciences, International Journal of Digital Earth, 11 (12), https://doi.org/10.1080/17538947.2017.1385652

2017

Martín, Y., Li, Z., & Cutter, S. L. (2017). Leveraging Twitter to gauge evacuation compliance: spatiotemporal analysis of Hurricane Matthew. PloS One, 12(7), https://doi.org/10.1371/journal.pone.0181701

Li Z., Huang Q., Carbone G., Hu F. (2017)  A High Performance Query Analytical Framework for Supporting Data-intensive Climate StudiesComputers, Environment and Urban Systems, 62(3), 210-221, https://doi.org/10.1016/j.compenvurbsys.2016.12.003

Li, Z., Hu, F., Schnase, J. L., Duffy, D. Q., Lee, T., Bowen, M. K., & Yang, C. (2017). A spatiotemporal indexing approach for efficient processing of big array-based climate data with MapReduceInternational Journal of Geographical Information Science, 31(1), 17-35, https://doi.org/10.1080/13658816.2015.1131830

Yang C., Huang Q., Li Z., Liu K., Fei Hu. (2017).  Big Data and cloud computing: innovation opportunities and challenges, International Journal of Digital Earth, 10(1),1-41, https://doi.org/10.1080/17538947.2016.1239771

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(B), 141-152, https://doi.org/10.1016/j.compenvurbsys.2014.06.004

2016

Li, Z., Yang, C., Liu, K., Hu, F., & Jin, B. (2016). Automatic Scaling Hadoop in the Cloud for Efficient Process of Big Geospatial DataISPRS International Journal of Geo-Information, 5(10), 173., https://doi.org/10.3390/ijgi5100173

Gui, Z., Yu, M., Yang, C., Jiang, Y., Chen, S., Xia, J., Huang, Q., Liu, K., Li, Z., Hassan, M.A. and Jin, B., (2016). Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation. PloS one, 11(4), https://doi.org/10.1371/journal.pone.0152250

2015

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

Xia J, Yang C, Liu K, Li Z., Sun M, Yu M, (2015). Forming a global monitoring mechanism and a spatiotemporal performance model for geospatial services, International Journal of Geographic Information Science, https://doi.org/10.1080/13658816.2014.968783

Before 2015

Xia J., Yang C., Liu K., Gui Z., Li Z., Huang Q., & Li R., (2014). Adopting cloud computing to optimize spatial web portals for better performance to support Digital Earth and other global geospatial initiativesInternational Journal of Digital Earth. 8(6). https://doi.org/10.1080/17538947.2014.929750

Gui Z., Yang C., Xia. J, Huang Q., Liu K., Li Z., Yu M., Zhou N., Jin B., (2014). A Service Brokering and Recommendation Mechanism for Better Selecting Cloud Services, PloS one, 9(8).  https://doi.org/10.1371/journal.pone.0105297

Xia J., Yang C., Gui Z., Liu K., Li Z., (2014). Optimizing an index with spatiotemporal patterns to support GEOSS Clearinghouse. International Journal of Geographical Information Science, 28(7), 1459-1481. https://doi.org/10.1080/13658816.2014.894195

Huang Q., Yang C., Liu K., Xia J., Xu C., Li J., Li Z., (2013). Evaluating open-source cloud computing solutions for geosciencesComputers & Geosciences, 59, 41-52. https://doi.org/10.1016/j.cageo.2013.05.001

Gong J., Wu H., Zhang T., Gui Z, Li Z., You  L., Shen  S., (2012). Geospatial Service Web: towards integrated cyberinfrastructure for GIScience. Geo-spatial Information Science, 15(2):73-84., https://doi.org/10.1080/10095020.2012.714098

Li Z., Yang C., Wu H., Li W., and Miao L., (2011). An optimized framework for seamlessly integrating OGC Web Services to support geospatial sciences, International Journal of Geographic Information Science, 25(4):595-613, https://doi.org/10.1080/13658816.2010.484811

Wu H., Li Z., Zhang H., Yan, C., & Shen S., (2011). Monitoring and evaluating the quality of Web Map Service resources for optimizing map composition over the internet to support decision makingComputers & Geosciences, 37(4), 485-494, https://doi.org/10.1016/j.cageo.2010.05.026

Yang C., Wu H., Huang Q., Li Z., and Li J., (2011). Using spatial principles to optimize distributed computing for enabling the physical science discoveries, Proceedings of National Academy of Sciences, 108(14): 5498-5503, https://doi.org/10.1073/pnas.0909315108 (spatial computing definition paper captured by Nobel Intent Blog)

Li W., Yang C., Nebert D., Raskin R., Houser P., Wu H., Li Z., (2011). Semantic-based web service discovery and chaining for building an Arctic spatial data infrastructureComputers & Geosciences, 37(11), 1752-1762., https://doi.org/10.1016/j.cageo.2011.06.024

Miao Li., Li Z., Li J., Yang C., (2012). An OPeNDAP-based System to Implement Earth Science Data Sharing, Journal of Nanjing University of Posts and Telecommunications,32(1):84-88. http://en.cnki.com.cn/Article_en/CJFDTotal-NJYD201201018.htm (in Chinese)

Li Z. and Xu J., (2012). Location Based Service Platform Construction Based on Cloud Computing. Geomatics World, 2012(1): 69-71. http://en.cnki.com.cn/Article_en/CJFDTOTAL-CHRK201201017.htm (in Chinese)

Li Z., Miao L, & Xiu W., (2010). The Integration of WMS and Google Earth using QuadKMLGeomatics & Spatial Information Technology, 5, 008. http://en.cnki.com.cn/Article_en/CJFDTOTAL-DBCH201005008.htm (in Chinese)

Miao L., Wu L. and Li Z., and Yang C., (2010). Integration and Interoperability of Distributed Geospatial Information Based on CSW and WMS. , Geography and Geo-Information Science, 26(3):11-14, http://www.en.cnki.com.cn/Article_en/CJFDTOTAL-DLGT201003004.htm(in Chinese)

Books

Li Z., Huang Q., Emrich C., (Eds.) (2021) Social Sensing and Big Data Computing for Disaster Management, Routledge/Taylor & Francis, ISBN: 978-0-367-61765-3

Li Z., Tang W., Huang Q., Shook E., Guan Q. (Eds.) (2020) Big Data Computing for Geospatial Applications, MPDI, https://doi.org/10.3390/books978-3-03943-245-5

Yang C., Yu M., Huang Q., Li Z., Sun M., Liu K., Jiang Y., Xia J., Hu F. (2017) Introduction to Programming and GIS Algorithms with Python and ArcGIS, CRC Press/Taylor & Francis. ISBN: 978-1466510081

Yang C., Huang Q., Li Z., Xu C., Liu K. (Eds.), (2013). Spatial Cloud Computing: A Practical Approach, CRC Press/Taylor & Francis

Articles in Books and Proceedings

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

Huang X., Xu D., Li Z., Wang C., (2020) Translating Multispectral Imagery to Nighttime Imagery via Conditional Generative Adversarial Networks, IEEE International Geoscience and Remote Sensing Symposium, July 19-24, 2020, Hawaii, USA.

Vayansky I., Kumar S., Li Z., (2019) An Evaluation of Geotagged Twitter Data during Hurricane Irma using Sentiment Analysis and Topic Modeling for Disaster Resilience, in 2019 IEEE International Symposium on Technology in Society (ISTAS) Proceedings, 15 – 16 November, Boston

Huang X., Wang C., Li Z., (2019) High-Resolution Population Grid in the CONUS using Microsoft Building Footprints: a feasibility study, in Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Geospatial Humanities, November 5, Chicago, Illinois, USA

Huang, X., C. Wang, and Li Z., (2019) Linking picture with text: tagging flood relevant tweets for rapid flood inundation mapping, Proceedings of the International Cartographic Association 2(45), doi: 10.5194/ica-proc-2-45-2019

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, USA.

Singleton S., Kumar S., Li Z. (2018), Twitter Analytics: Are the United States Coastal Regions Prepared for Climate Change? IEEE International Symposium on Technology and Society

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

Huang Q., Li Z., Li J., (2016), Mining Frequent Trajectory Patterns from Online Footprints, 7th ACM SIGSPATIAL International Workshop on GeoStreaming (IWGS), San Francisco, California, USA.

Yu, M., Yang, C., Li, Z., Liu, K., & Chen, S. (2015), Enabling the Acceleration of Dust Simulation using Job Scheduling Methods in a Cloud Environment. In Proceedings of the 13th International Conference on GeoComputation

Li Z., Yang C., Sun M., Li J., Xu C., Huang Q., & Liu K., (2013). A High Performance Web-Based System for Analyzing and Visualizing Spatiotemporal Data for Climate Studies. In W2GIS, Lecture Notes in Computer Science, Volume 7820 (pp. 190-198). Springer Berlin Heidelberg.

Liu K., Yang C., Li W., Li Z., Wu H., Rezgui A., & Xia J., (2011). The GEOSS Clearinghouse high performance search engine. In 2011 19th International Conference on Geoinformatics (pp. 1-4), IEEE.

Bambacus M., Yang C., Evans J., Li Z., Li W. and Huang Q., (2008). Sharing Earth science information to support the Global Earth Observing System of Systems (GEOSS). In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS08) (pp. 141-144), Boston, US.

Yang C., Liu K., Li Z., Li W., Wu H., Xia J., Huang Q., et al. (2014). GEOSS Clearinghouse: Integrating Geospatial Resources to Support the Global Earth Observation System of Systems, (2014). In Karimi, H. A. (Ed.), Big Data: Techniques and Technologies in Geoinformatics (pp. 31-54). CRC Press.

Yang, C., Sun, M., Liu, K., Huang, Q., Li, Z., Gui, Z., Jiang, Y., et al., (2014). Contemporary Computing Technologies for Processing Big Spatiotemporal Data. In Kwan M.P., Richardson D., Wang D., Zhou C.,(Eds.), Space-Time Integration in Geography and GIScience (pp. 327-351). Springer Netherlands.

Li, Z., Huang, Q., and Gui, Z., (2013). Enabling Technologies. In Yang C., Huang Q., Li Z., Xu C., Liu K(Eds.), Spatial cloud computing: a practical approach (pp. 33-48) CRC Press/Taylor & Francis

Huang, Q., Li, Z., Xia, J., Jiang, Y., Xu, C., Liu, K., et al., (2013). Accelerating Geocomputation with Cloud Computing. In Shi X., Kindratenko V., and Yang C. (Eds.), Modern Accelerator Technologies for Geographic Information Science (pp. 41-51). Springer US.

Li J., Li, Z., Sun M., Liu K., (2013). Cloud-enabling Climate@Home. In Yang C., Huang Q., Li Z., Xu C., Liu K.,(Eds.), Spatial cloud computing: a practical approach (pp. 143-160).  CRC Press/Taylor & Francis

Huang, Q., Li, Z., Liu K., Xia J., Jiang Y., Xu C., Yang C., (2013). Handling of Data, Computing, Concurrent and Spatiotemporal Intensities. In Yang C., Huang Q., Li Z., Xu C., Liu K.,(Eds.), Spatial cloud computing: a practical approach(pp. 275-294).  CRC Press/Taylor & Francis

Yang C., Huang Q., Gui Z., Li Z., Xu C., Jiang Y., Li J., (2013). Cloud Computing Research for Geosciences. In Yang C., Huang Q., Li Z., Xu C., Liu K.,(Eds.), Spatial cloud computing: a practical approach (pp. 295-310).  CRC Press/Taylor & Francis

Liu K., Huang Q., Xia J., Li Z., Lostritto P., 2013. How to User Cloud Computing. In Yang C., Huang Q., Li Z., Xu C., Liu K., (Eds.), Spatial cloud computing: a practical approach (pp. 51-74). CRC Press/Taylor & Francis

Liu K., Nebert D., Huang Q., Xia J., Li Z., 2013. Cloud-enabling GEOSS clearinghouse. In Yang C., Huang Q., Li Z., Xu C., Liu K., (Eds.), Spatial cloud computing: a practical approach (pp. 51-74). CRC Press/Taylor & Francis

Li, Z., W. Li, (2010). In Yang C., Wong D., Miao Q., Yang Run., (Eds.),  Geobrowser and spatial web portals. Advanced Geoinformation Science(pp. 234-239), CRC Press/Taylor and Francis

Yang C., Wu H., Huang Q., Li Z., J. Li, W. Li, L. Miao and M. Sun, (2011). WebGIS performance issues and solutions, ISPRS book on Advances in web-based GIS, mapping services and applications (pp. 121-138), London: Taylor & Francis

Shi, X., Nebert D., Zhang C., Yang H., Wu H., Zhao P., Li Z. et al. (2011). Geoinformation Infrastructure (GII). In Yang C., Wong D., Miao Q., and Yang R.  (Eds.), Advanced GeoInformation Science(pp. 205-274), CRC Press/Taylor and Francis

Other Publications

Li Z., Wang C., Emrich C., Guo D., 2016. Rapid Mapping of October 2015 South Carolina Flood using Social Media, Remote Sensing and Stream Gauges. In: The South Carolina Deluge: Lessons from a Watershed Disaster, Center for Resilience Studies, Northeastern University (pp. 52-62)

Wang C., Li Z., Emrich C., Remote sensing of surface wetness dynamics during the October 2015 South Carolina Flood, Congaree River Watershed. In: The South Carolina Deluge: Lessons from a Watershed Disaster, Center for Resilience Studies, Northeastern University (pp. 63-67)

Karami A., Li Z. (2016), Computational Framework for Tracking Reports, Opinions and Feelings of People in Social Media Before, During and After a Natural Disaster: Twitter Case Study in the 2015 South Carolina Flood, Available at https://sc.edu/about/offices_and_divisions/research/docs/sc_floods_project_summarybooklet.pdf (pp. 37-38)

 
Ph.D. Dissertations

Jiang Y. (2022), Quantifying Human Mobility Patterns During Disruptive Events with Big Data, (Committee: Drs. Zhenlong Li, Susan Cutter, Michael Hodgson, Qunying Huang )

Huang, X. (2020), Remote Sensing and Social Sensing for Improved Flood Awareness and Exposure Analysis in the Big Data Era, (Committee: Drs. Susan Wang, Zhenlong Li, Michael Hodgson, David Hitchcock)

Derakhshan, S. (2020) Spatio-Temporal Modeling of Earthquake Recovery (Committee: Drs. Susan Cutter, Cuizhen Wang, Zhenlong Li, Melanie Gall)

Martin, Y. (2019), Leveraging Geotagged Social Media to Monitor Spatial Behavior During Population Movements Triggered by Hurricanes (Committee: Drs. Susan L. Cutter, Zhenlong Li,  Jerry T. Mitchell, Christopher T. Emrich)

Li, Z. (2015). Optimizing Geospatial Cyberinfrastructure to Improve the Computing Capability for Climate Studies (Committee: Drs. Chaowei Yang, George Taylor,  Ruixin Yang,  Kirk Borne, John L. Schnase)

Master Theses

Ning H. (2019). Prototyping A Social Media Flooding Photo Screening System Based On Deep Learning and Crowdsourcing (Committee: Drs. Zhenlong Li, Michael E. Hodgson, Cuizhen Wang)

Vayansky, I. R. (2018). An Evaluation of Geotagged Twitter Data during Hurricane Irma using Sentiment Analysis and Topic Modeling for Disaster Resilience. (Committee: Drs. Sathish A.P Kumar, Zhenlong Li, William Jones )

Pham. E. (2018). Analysis of Evacuation Behaviors and Departure Timing for October 2016’s Hurricane Matthew. (Committee: Drs. Susan L. Cutter, Christopher Emrich,  Zhenlong Li )

Campbell. R.  (2018). Tweets About Tornado Warnings: A Spatiotemporal & Content Analysis (Committee: Drs. Susan L. Cutter, Zhenlong Li, Gregory Carbone)

Windsor M. (2017). A Web-based Decision Support Platform for Community Engagement in Water Resources Planning (Committee: Drs. Zhenlong Li, Jean Taylor Ellis)

Jiang Y. (2016). Urban Accessibility Measurement and Visualization—A Big Data Approach (Committee: Drs. Diansheng Guo, Zhenlong Li, Michael E. Hodgson)

Undergraduate Theses (Honors and Graduate with Distinction)

Finn Hagerty (2021), Tracking Population Movement using Geotagged Tweets to and from New York City and Los Angeles during the COVID-19 Pandemic,  (Committee: Drs. Zhenlong Li, Amir Karami)

Murph R. (2019), Steering Clear of Single-Occupancy Vehicles: Campus Transportation Demand Management Strategies for the University of South Carolina (Committee: Drs. Conor M. Harrison, Zhenlong Li)

 


Related Links

Google Scholar         ResearchGate

Translate »