Research Publications

  • Lu, D. N., He, H. D., Zhao, H. M., Lu, K. F., Peng, Z. R., & Li, J. (2023). Quantification of traffic-related carbon emission on elevated roads through on-road measurement. Environmental Research, 116200.https://doi.org/10.1016/j.envres.2023.116200



  • Yang, W., Cao, R., Ma, F., Wang, Z., Hu, X., Cai, M., … & Zhang, L. (2023). High-resolution distributions of traffic particles and personal inhalation dose estimation at different pedestrian overpasses. Atmospheric Pollution Research, 101786.https://doi.org/10.1016/j.apr.2023.101786



  • Liu, X., Shi, X. Q., Peng, Z. R., & He, H. D. (2023). Quantifying the effects of urban fabric and vegetation combination pattern to mitigate particle pollution in near-road areas using machine learning. Sustainable Cities and Society93, 104524. https://doi.org/10.1016/j.scs.2023.104524



  • Wu, C. L., Song, R. F., Zhu, X. H., Peng, Z. R., Fu, Q. Y., & Pan, J. (2023). A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network. Environmental Pollution, 121075.  https://doi.org/10.1016/j.envpol.2023.121075



  • Fang, X. R., Zhu, X. H., Li, X. Z., Peng, Z. R., Qingyao, H., He, H. D., … & Cheng, H. (2023). Assessing the effects of short-term traffic restriction policies on traffic-related air pollutants. Science of The Total Environment, 161451. https://doi.org/10.1016/j.scitotenv.2023.161451



  • Yang, X., Li, X., Lu, K., & Peng, Z. R. (2022). Integrating rural livelihood resilience and sustainability for post-disaster community relocation: a theoretical framework and empirical study. Natural Hazards, 1-29. https://doi.org/10.1007/s11069-022-05739-4



  • Zhu, X. H., Lu, K. F., Peng, Z. R., & Gao, H. O. (2022). Characterizing carbon emissions from China V and China VI gasoline vehicles based on portable emission measurement systems. Journal of Cleaner Production378, 134458. https://doi.org/10.1016/j.jclepro.2022.134458



  • Liu, X., Shi, X. Q., Li, X. B., & Peng, Z. R. (2022). Quantification of multifactorial effects on particle distributions at urban neighborhood scale using machine learning and unmanned aerial vehicle measurement. Journal of Cleaner Production378, 134494. https://doi.org/10.1016/j.jclepro.2022.134494



  • Zhao, H. M., He, H. D., Lu, K. F., Han, X. L., & Peng, Z. R. (2022). Characterizing the distribution pattern of submicron and coarse particles on high-density container truck roads through mobile monitoring. Atmospheric Pollution Research, 101561. https://doi.org/10.1016/j.apr.2022.101561



  • Zhang, T., Peng, Z.R., He, H. D., Zhang, S.J., Wu, Y., Horizontal profiles of size-segregated particle number concentration and black carbon beside a major roadway. Atmospheric Environment: X, 100187. https://doi.org/10.1016/j.aeaoa.2022.100187



  • Lei, C., Xu, J.Q., Chen, H., Sun, D.Q., Wang, B., Zheng, Y.N., Yang, X.D., & Peng, Z.R. (2022). Evaluation of the Spatial Effect of Network Resilience in the Yangtze River Delta: An Integrated Framework for Regional Collaboration and Governance under Disruption. Land 11, no. 8: 1359. https://doi.org/10.3390/land1108135



  • Liu, X., Peng, Z. R., Zhang, L. Y., & Chen, Q. (2022). Real-time and Coordinated UAV Path Planning for Road Traffic Surveillance: A Penalty-based Boundary Intersection Approach. International Journal of Control, Automation and Systems, 1-14. https://link.springer.com/article/10.1007/s12555-020-0565-8



  • Li, C., & Peng, Z. R. (2022). Spatial distributions of particulate matter in neighborhoods along the highway using unmanned aerial vehicle in Shanghai. Building and Environment211, 108754. https://doi.org/10.1016/j.buildenv.2022.108754



  • Zhang, Z., He, H. D., Yang, J. M., Wang, H. W., Xue, Y., & Peng, Z. R. (2022). Spatiotemporal evolution of NO2 diffusion in Beijing in response to COVID-19 lockdown using complex network. Chemosphere293, 133631. https://doi.org/10.1016/j.chemosphere.2022.133631



  • Li, B., Cao, R., He, H. D., Peng, Z. R., Qin, H., & Qin, Q. (2022). Three-dimensional diffusion patterns of traffic-related air pollutants on the roadside based on unmanned aerial vehicles monitoring. Building and Environment, 109159. https://doi.org/10.1016/j.buildenv.2022.109159



  • Wang, D., Wang, H.-W., Lu, K.-F., Peng, Z.-R., & Zhao, J. (2022). Regional prediction of ozone and fine particulate matter using diffusion convolutional recurrent neural network. International Journal of Environmental Research and Public Health, 19(7), 3988. https://doi.org/10.3390/ijerph19073988



  • Jiang, Y. H., Li, B., Li, X. B., Wang, D. S., & Peng, Z. R. (2022). Identification of the atmospheric boundary layer structure through vertical distribution of PM2. 5 obtained by unmanned aerial vehicle measurements. Atmospheric Environment, 119084. https://doi.org/10.1016/j.atmosenv.2022.119084



  • Lu, K. F., Wang, H. W., Li, X. B., Peng, Z. R., He, H. D., & Wang, Z. P. (2022). Assessing the effects of non-local traffic restriction policy on urban air quality. Transport Policy115, 62-74.  https://doi.org/10.1016/j.tranpol.2021.11.005



  • Zhu, X. H., Lu, K. F., Peng, Z. R., He, H. D., & Xu, S. Q. (2022). Spatiotemporal variations of carbon dioxide (CO2) at Urban neighborhood scale: Characterization of distribution patterns and contributions of emission sources. Sustainable Cities and Society, 78, 103646.https://doi.org/10.1016/j.scs.2021.103646



  • Liu, X., Shi, X. Q., He, H. D., & Peng, Z. R. (2022). Distribution characteristics of submicron particle influenced by vegetation in residential areas using instrumented unmanned aerial vehicle measurements. Sustainable Cities and Society78, 103616.  doi.org/10.1016/j.scs.2021.103616



  • Liu, X., Shi, X. Q., He, H. D., Li, X. B., & Peng, Z. R. (2021). Vertical distribution characteristics of particulate matter beside an elevated expressway by unmanned aerial vehicle measurements. Building and Environment206, 108330. https://doi.org/10.1016/j.buildenv.2021.108330.



  • J, Y., Peng, Z., & L, L. (2021). Real-Time Spatiotemporal Prediction and Imputation of Traffic Status Based on LSTM and Graph Laplacian Regularized Matrix Factorization. Transportation Research Part C, 129(203228). https://doi.org/10.1016/j.trc.2021.103228



  • Tanvir, M. R. A., & Peng, Z. R. (2021). Spatio-temporal variability in black carbon concentrations at highway toll plaza: Comparison between manual and electronic toll lanes. Atmospheric Pollution Research, 12(1), 286-294. https://doi.org/10.1016/j.apr.2020.09.010



  • Zheng, T., Li, B., Li, X. B., Wang, Z., Li, S. Y., & Peng, Z. R. (2021). Vertical and horizontal distributions of traffic-related pollutants beside an urban arterial road based on unmanned aerial vehicle observations. Building and Environment187, 107401. https://doi.org/10.1016/j.buildenv.2020.107401



  • Zheng, T., Wang, H. W., Li, X. B., Peng, Z. R., & He, H. D. (2021). Impacts of traffic on roadside particle variations in varied temporal scales. Atmospheric Environment253, 118354. https://doi.org/10.1016/j.atmosenv.2021.118354



  • Luo, Z. G., Wang, Z. Y., Wang, H. W., He, H. D., & Peng, Z. R. (2021). Characterizing spatiotemporal distributions of black carbon and PM2. 5 at a toll station: Observations on manual and electronic toll collection lanes. Building and Environment, 107933. https://doi.org/10.1016/j.buildenv.2021.107933



  • Jia, Y. P., Lu, K. F., Zheng, T., Li, X. B., Liu, X., Peng, Z. R., & He, H. D. (2021). Effects of roadside green infrastructure on particle exposure: A focus on cyclists and pedestrians on pathways between urban roads and vegetative barriers. Atmospheric Pollution Research12(3), 1-12. https://doi.org/10.1016/j.apr.2021.01.017



  • Han, Y., Chen, C., Peng, Z. R., & Mozumder, P. (2021). Evaluating impacts of coastal flooding on the transportation system using an activity-based travel demand model: a case study in Miami-Dade County, FL. Transportation, 1-22. https://doi.org/10.1007/s11116-021-10172-w



  • Zheng, T., Jia, Y. P., Zhang, S., Li, X. B., Wu, Y., Wu, C. L., … & Peng, Z. R. (2021). Impacts of vegetation on particle concentrations in roadside environments. Environmental Pollution282, 117067. https://doi.org/10.1016/j.envpol.2021.117067



  • Zhai, W., Liu, M., Fu, X., & Peng, Z. R. (2021). American Inequality Meets COVID-19: Uneven Spread of the Disease across Communities. Annals of the American Association of Geographers, 1-21. https://doi.org/10.1080/24694452.2020.1866489



  • Huang, H., Yang, H., Chen, Y., Chen, T., Bai, L., & Peng, Z. (2021). Urban Green Space Optimization Based on a Climate Health Risk Appraisal-A case study of Beijing city, China. Urban Forestry & Urban Greening, 127154. https://doi.org/10.1016/j.ufug.2021.127154



  • Kapucu, N., Beaudet, S., Chang, N. B., Qiu, J., & Peng, Z. R. (2021). Partnerships and Network Governance for Urban Food-Energy-Water (FEW) Nexus. International Journal of Public Administration, 1-14. https://doi.org/10.1080/01900692.2021.1967981



  • Zhai, W., Peng, Z. R., & Bai, X. (2021). Prototypical Resilience Projects for Postdisaster Recovery Planning: From Theory to Action. Journal of Planning Education and Research, 0739456X211048928. https://doi.org/10.1177/0739456X211048928



  • Huang, H., Yang, H., Chen, Y., Chen, T., Bai, L., & Peng, Z. R. (2021). Urban green space optimization based on a climate health risk appraisal–A case study of Beijing city, China. Urban Forestry & Urban Greening62, 127154. https://doi.org/10.1016/j.ufug.2021.127154



  • Han, Y., Mao, L., Chen, X., Zhai, W., Peng, Z. R., & Mozumder, P. (2021). Agent‐based Modeling to Evaluate Human–Environment Interactions in Community Flood Risk Mitigation. Risk Analysis. https://doi.org/10.1111/risa.13854



  • Wu, C. L., Wang, H. W., Cai, W. J., Ni, A. N., & Peng, Z. R. (2021). Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China. Building and environment, 194, 107718. https://doi.org/10.1016/j.buildenv.2021.107718



  • Song, R. F., Wang, D. S., Li, X. B., Li, B., & Peng, Z. R. (2021). Characterizing vertical distribution patterns of PM2. 5 in low troposphere of Shanghai city, China: Implications from the perspective of unmanned aerial vehicle observations. Atmospheric Environment265, 118724. https://doi.org/10.1016/j.atmosenv.2021.118724



  • Cai, Jin, W., Wang, H., Wu, C., Lu, K., Peng, Z., & He, H. (2021). Characterizing the Interruption-Recovery Patterns of Urban Air Pollution under the COVID-19 Lockdown in China. Building and Environment, 205(108231). https://doi.org/10.1016/j.buildenv.2021.108231



  • Zhai, W., & Peng, Z. R. (2020). Where to buy a house in the United States amid COVID-19?Environment and Planning A: Economy and Space, 0308518X20946041.



  • Li, X. B., Peng, Z. R., Lu, Q. C., Wang, D., Hu, X. M., Wang, D., … & He, H. (2020). Evaluation of unmanned aerial system in measuring lower tropospheric ozone and fine aerosol particles using portable monitorsAtmospheric Environment222, 117134.



  • Yu, H., & Peng, Z. R. (2020). The impacts of built environment on ridesourcing demand: A neighbourhood level analysis in Austin, Texas. Urban Studies57(1), 152-175.



  • Gao, Y., Wang, Z., Li, C. Y., Zheng, T., & Peng, Z. R. (2020). Assessing neighborhood variations in ozone and PM2. 5 concentrations using decision tree method. Building and Environment, 107479. https://doi.org/10.1016/j.buildenv.2020.107479



  • Tanvir, M. R. A., & Peng, Z. R. (2020). Spatio-temporal variability in black carbon concentrations at highway toll plaza: Comparison between manual and electronic toll lanes. Atmospheric Pollution Research. https://doi.org/10.1016/j.apr.2020.09.010



  • Cao, R., Li, B., Wang, H. W., Tao, S., Peng, Z. R., & He, H. D. (2020). Vertical and Horizontal Profiles of Particulate Matter and Black Carbon Near Elevated Highways Based on Unmanned Aerial Vehicle Monitoring. Sustainability12(3), 1204. https://doi.org/10.3390/su12031204



  • Tanvir, M. R. A., & Peng, Z. R. (2020). Spatio-temporal variability in black carbon concentrations at highway toll plaza: Comparison between manual and electronic toll lanes. Atmospheric Pollution Research.



  • Han, Y., Ash, K., Mao, L., & Peng, Z. R. (2020). An agent-based model for community flood adaptation under uncertain sea-level rise. Climatic Change, 1-20. https://doi.org/10.1007/s10584-020-02802-6



  • Wang, H. W., Li, X. B., Wang, D., Zhao, J., & Peng, Z. R. (2020). Regional prediction of ground-level ozone using a hybrid sequence-to-sequence deep learning approachJournal of Cleaner Production253, 119841.



  • Zhai, W., & Peng, Z. R. (2020). Damage assessment using Google Street View: Evidence from Hurricane Michael in Mexico Beach, FloridaApplied Geography123, 102252.



  • Chen, Q., Li, X. B., Song, R., Wang, H. W., Li, B., He, H. D., & Peng, Z. R. (2020). Development and utilization of hexacopter unmanned aerial vehicle platform to characterize vertical distribution of boundary layer ozone in wintertimeAtmospheric Pollution Research.



  • Wang, H. W., Peng, Z. R., Wang, D., Meng, Y., Wu, T., Sun, W., & Lu, Q. C. (2020). Evaluation and prediction of transportation resilience under extreme weather events: A diffusion graph convolutional approachTransportation Research Part C: Emerging Technologies115, 102619.



  • Zhai, W., Liu, M., & Peng, Z. R. (2020). Social distancing and inequality in the United States amid COVID-19 outbreakEnvironment and Planning A: Economy and Space, 0308518X20932576.



  • Cao, R., Li, B., Wang, Z., Peng, Z. R., Tao, S., & Lou, S. (2020). Using a distributed air sensor network to investigate the spatiotemporal patterns of PM2. 5 concentrationsEnvironmental Pollution, 114549.



  • Zhai, W., Peng, Z. R., & Yuan, F. (2020). Examine the effects of neighborhood equity on disaster situational awareness: Harness machine learning and geotagged Twitter dataInternational Journal of Disaster Risk Reduction, 101611.



  • Lu, K. F., He, H. D., Wang, H. W., Li, X. B., & Peng, Z. R. (2020). Characterizing temporal and vertical distribution patterns of traffic-emitted pollutants near an elevated expressway in urban residential areasBuilding and Environment172, 106678.



  • Chen, Q., Wang, D., Li, X., Li, B., Song, R., He, H., & Peng, Z. (2019). Vertical Characteristics of Winter Ozone Distribution within the Boundary Layer in Shanghai Based on Hexacopter Unmanned Aerial Vehicle PlatformSustainability11(24), 7026.



  • Li, C., Wang, Z., Li, B., Peng, Z. R., & Fu, Q. (2019). Investigating the relationship between air pollution variation and urban form. Building and Environment147, 559-568.



  • Tang, J., Zhu, Y., Huang, Y., Peng, Z. R., & Wang, Z. (2019). Identification and interpretation of spatial–temporal mismatch between taxi demand and supply using global positioning system data. Journal of Intelligent Transportation Systems23(4), 403-415. DOI: 10.1080/15472450.2018.1518137



  • Liu, X., Peng, Z. R., & Zhang, L. Y. (2019). Real-time uav rerouting for traffic monitoring with decomposition based multi-objective optimization. Journal of Intelligent & Robotic Systems94(2), 491-501.



  • Tang, J., Zhu, Y., Huang, Y., Peng, Z. R., & Wang, Z. (2019). Identification and interpretation of spatial–temporal mismatch between taxi demand and supply using global positioning system data. Journal of Intelligent Transportation Systems23(4), 403-415. DOI: 10.1080/15472450.2018.1518137.



  • Zhai, W., Bai, X., Peng, Z. R., & Gu, C. (2019). A bottom-up transportation network efficiency measuring approach: A case study of taxi efficiency in New York CityJournal of Transport Geography80, 102502.



  • Zhai, W., Bai, X., Shi, Y., Han, Y., Peng, Z. R., & Gu, C. (2019). Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs. Computers, Environment and Urban Systems74, 1-12.



  • Fu, X., & Peng, Z. R. (2019). Assessing the sea-level rise vulnerability in coastal communities: A case study in the Tampa Bay Region, US. Cities88, 144-154.



  • Li, B., Li, X. B., Li, C., Zhu, Y., Peng, Z. R., Wang, Z., & Lu, S. J. (2019). Impacts of wind fields on the distribution patterns of traffic emitted particles in urban residential areas. Transportation Research Part D: Transport and Environment68, 122-136.



  • Fu, X., Sun, B., Frank, K., & Peng, Z. R. (2019). Evaluating sea-level rise vulnerability assessments in the USA. Climatic Change155(3), 393-415.



  • Li, B., Cao, R., Wang, Z., Song, R. F., Peng, Z. R., Xiu, G., & Fu, Q. (2019). Use of Multi-Rotor Unmanned Aerial Vehicles for Fine-Grained Roadside Air Pollution Monitoring. Transportation Research Record2673(7), 169-180.



  • Zhai, W., Bai, X., Peng, Z. R., & Gu, C. (2019). From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region. Journal of Transport Geography78, 41-55.



  • Yu, H., & Peng, Z. R. (2019). Exploring the spatial variation of ridesourcing demand and its relationship to built environment and socioeconomic factors with the geographically weighted Poisson regression. Journal of Transport Geography, 75, 147-163.



  • Yu, H., & Peng, Z. R. (2019). Exploring the spatial variation of ridesourcing demand and its relationship to built environment and socioeconomic factors with the geographically weighted Poisson regression. Journal of Transport Geography75, 147-163.



  • Han, Y., & Peng, Z. R. (2019). The integration of local government, residents, and insurance in coastal adaptation: An agent-based modeling approachComputers, Environment and Urban Systems76, 69-79.



  • Song, J., Fu, X., Wang, R., Peng, Z. R., & Gu, Z. (2018). Does planned retreat matter? Investigating land use change under the impacts of flooding induced by sea level rise. Mitigation and Adaptation Strategies for Global Change23(5), 703-733. https://doi.org/10.1007/s11027-017-9756-x 



  • Wang, H. W., Peng, Z. R., Lu, Q. C., Sun, D. J., & Bai, C. (2018). Assessing effects of bus service quality on passengers’ taxi-hiring behavior. Transport33(4), 1030-1044. doi: 10.3846/16484142.2016.1275786



  • Wang, Z., Wang, D., Peng, Z. R., Cai, M., Fu, Q., & Wang, D. (2018). Performance assessment of a portable nephelometer for outdoor particle mass measurement. Environmental Science: Processes & Impacts20(2), 370-383. DOI: 10.1039/C7EM00336F.



  • Li, X. B., Wang, D. S., Lu, Q. C., Peng, Z. R., & Wang, Z. Y. (2018). Investigating vertical distribution patterns of lower tropospheric PM2. 5 using unmanned aerial vehicle measurements. Atmospheric Environment173, 62-71. https://doi.org/10.1016/j.atmosenv.2017.11.009



  • Jiang, R., Lu, Q. C., & Peng, Z. R. (2018). A station-based rail transit network vulnerability measure considering land use dependency. Journal of Transport Geography66, 10-18.



  • Li, B., Zhu, Y., Wang, Z., Li, C., Peng, Z. R., & Ge, L. (2018). Use of multi-rotor unmanned aerial vehicles for radioactive source search. Remote Sensing10(5), 728.



  • Wang, Z., Zhong, S., Peng, Z. R., & Cai, M. (2018). Fine-scale variations in PM2. 5 and black carbon concentrations and corresponding influential factors at an urban road intersection. Building and Environment, 141, 215-225.



  • Li, X. B., Wang, D., Lu, Q. C., Peng, Z. R., Fu, Q., Hu, X. M., … & Wang, D. S. (2018). Three-dimensional analysis of ozone and PM 2.5 distributions obtained by observations of tethered balloon and unmanned aerial vehicle in Shanghai, China. Stochastic Environmental Research and Risk Assessment32(5), 1189-1203. DOI:1007/s00477-018-1524-2.



  • Yu, H., Jiao, J., Houston, E., & Peng, Z. R. (2018). Evaluating the relationship between rail transit and industrial agglomeration: An observation from the Dallas-fort worth region, TX. Journal of Transport Geography67, 33-52.



  • Wang, Z., Lu, Q. C., He, H. D., Wang, D., Gao, Y., & Peng, Z. R. (2017). Investigation of the spatiotemporal variation and influencing factors on fine particulate matter and carbon monoxide concentrations near a road intersection. Frontiers of Earth Science11(1), 63-75. doi: 10.1007/s11707-016-0564-5



  • Jiang, B., Liang, S., Peng, Z. R., Cong, H., Levy, M., Cheng, Q., … & Remais, J. V. (2017). Transport and public health in China: the road to a healthy future. The Lancet390(10104), 1781-1791. http://dx.doi.org/10.1016/S0140-6736(17)31958-X



  • Zhao, L., Song, J., & Peng, Z. R. (2017). Modeling land-use change and population relocation dynamics in response to different sea level rise scenarios: Case study in Bay County, Florida. Journal of Urban Planning and Development143(3), 04017012. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000398



  • Gao, Y., Wang, Z., Lu, Q. C., Liu, C., Peng, Z. R., & Yu, Y. (2017). Prediction of vertical PM 2.5 concentrations alongside an elevated expressway by using the neural network hybrid model and generalized additive model. Frontiers of Earth Science11(2), 347-360. doi: 10.1007/s11707-016-0593-0



  • Deng, Y., Young, C., Fu, X., Song, J., & Peng, Z. R. (2017). The integrated impacts of human activities and rising sea level on the saltwater intrusion in the east coast of the Yucatan Peninsula, Mexico. Natural Hazards85(2), 1063-1088. doi:10.1007/s11069-016-2621-5



  • Fu, X., Gomaa, M., Deng, Y., & Peng, Z. R. (2017). Adaptation planning for sea level rise: a study of US coastal cities. Journal of environmental planning and management60(2), 249-265. doi:10.1080/09640568.2016.1151771



  • Peng, C., Yuan, M., Gu, C., Peng, Z., & Ming, T. (2017). A review of the theory and practice of regional resilience. Sustainable Cities and Society29, 86-96. https://doi.org/10.1016/j.scs.2016.12.003



  • Li, L., Lu, Q. C., Chang, Y. T., & Peng, Z. R. (2017). A Compositional Analysis of Unbalanced Usages of Multiple Left-turn Lanes. Promet-Traffic&Transportation29(3), 287-298. https://doi.org/10.7307/ptt.v29i3.2093



  • Song, J., Fu, X., Gu, Y., Deng, Y., & Peng, Z. R. (2017). An examination of land use impacts of flooding induced by sea level rise. Natural Hazards & Earth System Sciences17(3). doi:10.5194/nhess-17-315-2017



  • Li, X. B., Wang, D. S., Lu, Q. C., Peng, Z. R., Lu, S. J., Li, B., & Li, C. (2017). Three-dimensional investigation of ozone pollution in the lower troposphere using an unmanned aerial vehicle platform. Environmental pollution224, 107-116. doi: 10.1016/j.envpol.2017.01.064



  • Sun, B., Yu, H., Peng, Z. R., & Gao, Y. (2017). High-Speed Rail and Manufacturing Agglomeration: Evidence from Beijing–Guangzhou High-Speed Rail in China. Transportation Research Record2606(1), 86-95. https://doi.org/10.3141%2F2606-12



  • Fu, X., Song, J., Sun, B., & Peng, Z. R. (2016). “Living on the edge”: Estimating the economic cost of sea level rise on coastal real estate in the Tampa Bay region, Florida. Ocean & Coastal Management133, 11-17. doi: 10.1016/j.ocecoaman.2016.09.009.



  • Song, J., Peng, Z. R., Zhao, L., & Hsu, C. H. (2016). Developing a theoretical framework for integrated vulnerability of businesses to sea level rise. Natural Hazards84(2), 1219-1239. doi: 10.1007/s11069-016-2483-x



  • Shen, S., Feng, X., & Peng, Z. R. (2016). A framework to analyze vulnerability of critical infrastructure to climate change: the case of a coastal community in Florida. Natural Hazards84(1), 589-609. doi: 10.1007/s11069-016-2442-6



  • Liu, C., Henderson, B. H., Wang, D., Yang, X., & Peng, Z. R. (2016). A land use regression application into assessing spatial variation of intra-urban fine particulate matter (PM2. 5) and nitrogen dioxide (NO2) concentrations in City of Shanghai, China. Science of The Total Environment565, 607-615. doi:10.1016/j.scitotenv.2016.03.189



  • Li, X. B., Lu, Q. C., Lu, S. J., He, H. D., Peng, Z. R., Gao, Y., & Wang, Z. Y. (2016). The impacts of roadside vegetation barriers on the dispersion of gaseous traffic pollution in urban street canyons. Urban forestry & urban greening17, 80-91. doi:10.1016/j.ufug.2016.03.006



  • WANG, H. W., CHENG, K., LU, Q. C., & PENG, Z. R. (2016). Improved Model of Start-Wave Velocity at Intersections Based on Unmanned Aerial Vehicle DataJournal of Donghua University (Eng. Ed.) Vol33(1).



  • Zhao, L., & Peng, Z. R. (2015). LandSys II: agent-based land use–forecast model with artificial neural networks and multiagent model. Journal of Urban Planning and Development141(4), 04014045. doi:1061/(ASCE)UP.1943-5444.0000255



  • Peng, Z. R., Wang, D., Wang, Z., Gao, Y., & Lu, S. (2015). A study of vertical distribution patterns of PM2. 5 concentrations based on ambient monitoring with unmanned aerial vehicles: A case in Hangzhou, China. Atmospheric Environment123, 357-369. doi:10.1016/j.atmosenv.2015.10.074



  • Wang, Z., He, H. D., Lu, F., Lu, Q. C., & Peng, Z. R. (2015). Hybrid model for prediction of carbon monoxide and fine particulate matter concentrations near a road intersection. Transportation Research Record2503(1), 29-38. doi:10.3141/2503-04



  • Wang, Z., Lu, F., Lu, Q. C., Wang, D., & Peng, Z. R. (2015). Fine-scale estimation of carbon monoxide and fine particulate matter concentrations in proximity to a road intersection by using wavelet neural network with genetic algorithm. Atmospheric Environment104, 264-272. doi:10.1016/j.atmosenv.2014.12.058



  • Peng, C., Ming, T., Tao, Y., & Peng, Z. (2015). Numerical analysis on the thermal environment of an old city district during urban renewal. Energy and Buildings89, 18-31. doi:10.1016/j.enbuild.2014.12.023



  • Bai, C., Peng, Z. R., Lu, Q. C., & Sun, J. (2015). Dynamic bus travel time prediction models on road with multiple bus routes. Computational intelligence and neuroscience2015. http://dx.doi.org/10.1155/2015/432389.



  • Sun, D. J., Xu, Y., & Peng, Z. R. (2015). Timetable optimization for single bus line based on hybrid vehicle size model. Journal of Traffic and Transportation Engineering (English Edition)2(3), 179-186. https://doi.org/10.1016/j.jtte.2015.03.006



  • Ni, X. Y., Sun, D., & Peng, Z. R. (2015). An improved incremental assignment model for parking variable message sign location problem. Journal of Advanced Transportation49(7), 817-828. doi:10.1002/atr.1305



  • Lu, Q. C., Peng, Z. R., & Zhang, J. (2015). Identification and prioritization of critical transportation infrastructure: case study of coastal flooding. Journal of Transportation Engineering141(3), 04014082. doi:10.1061/(ASCE)TE.1943-5436.0000743



  • Peng, C., Ming, T., Cheng, J., Wu, Y., & Peng, Z. R. (2015). Modeling Thermal Comfort and Optimizing Local Renewal Strategies—A Case Study of Dazhimen Neighborhood in Wuhan City. Sustainability7(3), 3109-3128. doi:10.3390/su7033109



  • Wang, B., Su, S., Peng, Z., & Yang, F. (2015). Coastal wetlands impact assessment of sea level rise. Tongji Daxue Xuebao/Journal of Tongji University. 43 (4) 569-575. DOI: 10.11908/j.issn.0253-374x.2015.04.013.



  • Wang, Q., Liu, Z., & Peng, Z. (2015). A PSO-SVM Model for short-term travel time prediction based on Bluetooth TechnologyJ. Harbin Inst. Technol22, 7-14.



  • Chen, X. Z., Lu, Q. C., Peng, Z. R., & Ash, J. E. (2015). Analysis of transportation network vulnerability under flooding disasters. Transportation research record2532(1), 37-44. https://doi.org/10.3141%2F2532-05



  • Lu, Q. C., Peng, Z. R., Zhang, L., & Wang, Z. (2014). Economic analyses of sea-level rise adaptation strategies in transportation considering spatial autocorrelation. Transportation Research Part D: Transport and Environment33, 87-94. doi:10.1016/j.trd.2014.09.004



  • Lu, Q. C., Zhang, J., Peng, Z. R., & Rahman, A. S. (2014). Inter-city travel behaviour adaptation to extreme weather events. Journal of Transport Geography41, 148-153. doi: 10.1016/j.jtrangeo.2014.08.016



  • Lin-Jun, Y., Ya-Lan, L., Zhong-Ren, P., Meng Meng, L., & Yu-Huan, R. (2014, March). A Modelling Framework for estimating Road Segment Based On-Board Vehicle Emissions. In IOP Conference Series: Earth and Environmental Science (EES) (Vol. 17, No. 1). doi:10.1088/1755-1315/17/1/012253



  • Zhang, D. Z., Peng, Z. R., & Sun, D. J. (2014). A comprehensive taxi assessment index using floating car dataJournal of Harbin Institute of Technology21(1), 7-16.



  • Zhao, L., Peng, Z. R., Yang, F., & Shen, S. (2014). A bid-rent land-use adaptation model for mitigating road network vulnerability and traffic emissions. International Journal of Environmental Science and Technology11(8), 2359-2368. doi: 10.1007/s13762-014-0642-8



  • Zhang, D. Z., & Peng, Z. R. (2014). Near-road fine particulate matter concentration estimation using artificial neural network approach. International Journal of Environmental Science and Technology11(8), 2403-2412. doi: 10.1007/s13762-014-0565-4



  • Xu, T. D., Hao, Y., Peng, Z. R., & Sun, L. J. (2014). Corrigendum: Modeling probabilistic traffic breakdown on congested freeway flow. Canadian Journal of Civil Engineering41(2), 181-181. doi:10.1139/cjce2014-0009



  • Xu, T., Hao, Y., Peng, Z., & Sun, L. (2013). Anticipatory traveller information system for freeway-arterial networks. IET Intelligent Transport Systems8(3), 286-297. doi:10.1049/iet-its.2012.0067



  • Xu, T. D., Hao, Y., Peng, Z. R., & Sun, L. J. (2013). Modeling probabilistic traffic breakdown on congested freeway flow. Canadian Journal of Civil Engineering40(10), 999-1008. doi:10.1139/cjce-2012-0067



  • CHANG, J. J., PENG, Z. R., & SUN, J. (2013). Freight Vehicle Routing Optimization for Sporadic Orders Using Floating Car DataJournal of Donghua University (Eng. Ed.) Vol30(2).



  • Zhang, D. Z., Sun, J., & Peng, Z. R. (2013). Urban taxi goodness index and system implementation of GISJ Transp Syst Eng Inf Technol13(1), 87-96.



  • Linjun, Y., Danfeng, S., Zhongren, P., & Hong, L. I. (2013). A cellular automata land use model based on localized transition rules. Geographical Research32(4), 671-682.(In Chinese). doi: 10.11821/yj2013040010



  • Liu, X. F., Peng, Z. R., Chang, Y. T., & Zhang, L. Y. (2012). Multi-objective evolutionary approach for UAV cruise route planning to collect traffic information. Journal of central south university19(12), 3614-3621. doi: 10.1007/s11771-012-1449-8



  • Jian, S. U. N., Zhang, L., Chunlu, P. E. N. G., Zhongren, P. E. N. G., & Meng, X. U. (2012). CA-based urban land use prediction model: a case study on orange county, Florida, US. Journal of Transportation Systems Engineering and Information Technology12(6), 85-92. doi: 10.1016/S1570-6672(11)60234-1



  • Xu, X., Li, X., Hu, Y., & Peng, Z. (2012). A novel algorithm to identifying vehicle travel path in elevated road area based on GPS trajectory data. Frontiers of Earth Science6(4), 354-363. doi:10.1007/s11707-012-0340-0



  • Yu, L. J., Sun, D. F., Peng, Z. R., & Zhang, J. (2012). A hybrid system of expanding 2D GIS into 3D space. Cartography and Geographic Information Science39(3), 140-153. doi:10.1559/15230406393140



  • Xu, T. D., Hao, Y., Peng, Z. R., & Sun, L. J. (2012). Real-time travel time predictor for route guidance consistent with driver behavior. Canadian Journal of Civil Engineering39(10), 1113-1124. doi:1139/l2012-092



  • Zhao, L., & Peng, Z. R. (2012). LandSys: an agent-based Cellular Automata model of land use change developed for transportation analysis. Journal of Transport Geography25, 35-49. doi:10.1016/jtrangeo.2012.07.006



  • Lu, Q. C. (2012). China’s public transportation: problems, policies, and prospective of sustainabilityInstitute of Transportation Engineers. ITE Journal82(5), 36.



  • Lu, Q. C., Peng, Z. R., & Du, R. (2012). Economic analysis of impacts of sea level rise and adaptation strategies in transportation. Transportation research record2273(1), 54-61. doi:10.3141/2273-07



  • Zhang, L. Y., Peng, Z. R., Sun, D., & Liu, X. (2012). Rule-based forecasting of traffic flow for large-scale road networks. Transportation research record2279(1), 3-11. https://doi.org/10.3141%2F2279-01



  • Xu, T., Hao, Y., Peng, Z., & Sun, L. (2012). Automatic Calibration of Behavioral Parameters for Variable Message Sign–Based Route Guidance Consistent with Driver Behavior. Transportation research record2321(1), 55-65. doi: 10.3141/2321-08



  • Xu, T. D., Sun, L. J., Peng, Z. R., & Hao, Y. (2011). Integrated route guidance and ramp metering consistent with drivers’ en-route diversion behaviour. IET intelligent transport systems5(4), 267-276. doi:10.1049/iet-its.2011.0073



  • Xu, T. D., Sun, L. J., Peng, Z. R., & Hao, Y. (2011). Modelling drivers’ en-route diversion behaviour under variable message sign messages using real detected traffic data. IET intelligent transport systems5(4), 294-301. doi:10.1049/iet-its.2011.0060



  • Jian Daniel, S. U. N., Qiong, L. I. U., & Zhongren, P. E. N. G. (2011). Research and analysis on causality and spatial-temporal evolution of urban traffic congestions—a case study on Shenzhen of China. Journal of Transportation Systems Engineering and Information Technology11(5), 86-93. doi:10.1016/S1570-6672(10)60143-2



  • Lu, Q. C., & Peng, Z. R. (2011). Vulnerability analysis of transportation network under scenarios of sea level rise. Transportation research record2263(1), 174-181. doi:10.3141/2263-19



  • Sun, D., Peng, Z. R., Shan, X., Chen, W., & Zeng, X. (2011). Development of web-based transit trip-planning system based on service-oriented architecture. Transportation research record2217(1), 87-94. doi:10.3141/2217-11



  • Xu, T., Sun, L., & Peng, Z. R. (2011). Empirical analysis and modeling of drivers’ response to variable message signs in shanghai, china. Transportation research record2243(1), 99-107. doi:10.3141/2243-12



  • Xu, X., & Peng, Z. (2011, June). The K-function analysis of space-time point pattern on road network. In 2011 19th International Conference on Geoinformatics (pp. 1-5). IEEE. doi:10.1109/GeoInformatics.2011.5981103



  • Bin, Y., Li, Y., & Peng, Z. R. (2010). Multiple trip information based spatial domain optimisation for power management of plug-in hybrid electric vehicles. International Journal of Electric and Hybrid Vehicles2(4), 259-281. doi:10.1504/IJEHV.2010.03498



  • Zhao, L., & Peng, Z. R. (2010). Integrated bilevel model to explore interaction between land use allocation and transportation. Transportation research record2176(1), 14-25. doi:10.3141/2176-02



  • Gong, Q., Li, Y., & Peng, Z. R. (2009). Trip based optimal power management of plug-in hybrid electric vehicle with advanced traffic modelingSAE International journal of engines1(1), 861-872.



  • Zhang, C., Peng, Z. R., Zhao, T., & Li, W. (2008). Transforming transportation data models from UML to OWL ontological representation. Journal of Transport Research Board: Transport Research Record2064, 81-89. doi:10.3141/2064-11



  • Peng, Z. R., Zhu, Y., & Song, S. (2008). Mobility of the Chinese urban poor: a case study of Hefei City. Chinese Economy41(1), 36-57. doi:10.2753/CES-1097-1475410102



  • Huang, R., & Peng, Z. R. (2008). A spatiotemporal data model for dynamic transit networks. International Journal of Geographical Information Science22(5), 527-545. doi:10.1080/13658810701492399



  • Peng, Z. R., & Kim, E. (2008). A standard-based integration framework for distributed transit trip planning systems. Journal of Intelligent Transportation Systems12(1), 13-28. doi:10.1080/15472450701849642



  • Gong, Q., Li, Y., & Peng, Z. R. (2008). Trip-based optimal power management of plug-in hybrid electric vehicles. IEEE Transactions on vehicular technology57(6), 3393-3401. doi:10.1109/TVT.2008.921622



  • Zhao, T., Zhang, C., Wei, M., & Peng, Z. R. (2008, September). Ontology-based geospatial data query and integration. In International Conference on Geographic Information Science (pp. 370-392). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87473-7_24



  • Pucher, J., Peng, Z. R., Mittal, N., Zhu, Y., & Korattyswaroopam, N. (2007). Urban transport trends and policies in China and India: impacts of rapid economic growth. Transport reviews27(4), 379-410. doi:10.1080/01441640601089988



  • Peng, Z. R. (2005). A proposed framework for feature‐level geospatial data sharing: a case study for transportation network data. International Journal of Geographical Information Science19(4), 459-481. doi:10.1080/13658810512331319127



  • Peng, Z. R., Hawks, S., & West, K. (2005). Use of planning support software in transit services: A state-of-practice survey. Transportation research record1927(1), 126-136. doi:10.3141/1927-15



  • Sanchez, T. W., Shen, Q., & Peng, Z. R. (2004). Transit mobility, jobs access and low-income labour participation in US metropolitan areas. Urban Studies41(7), 1313-1331. doi:10.1080/0042098042000214815



  • Peng, Z. R., & Zhang, C. (2004). The roles of geography markup language (GML), scalable vector graphics (SVG), and Web feature service (WFS) specifications in the development of Internet geographic information systems (GIS). Journal of Geographical Systems6(2), 95-116. doi:10.1007/s10109-004-0129-0



  • Peng, Z. R., Guequierre, N., & Blakeman, J. C. (2004). Motorist response to arterial variable message signs. Transportation research record1899(1), 55-63. doi:10.3141/1899-07



  • Peng, Z. R. (2003, January). A Framework of Feature-Level Transportation Geospatial Data Sharing Systems. In Transportation Research Board Annual Meeting January.



  • Zhang, C., Li, W., Day, M. J., & Peng, Z. R. (2003). GML-based interoperable geographical databases. Cartography32(2), 1-16. doi:10.1080/00690805.2003.9714249



  • Peng, Z. R., & Tsou, M. H. (2003). Internet GIS: distributed geographic information services for the internet and wireless networks. John Wiley & Sons.



  • Peng, Z. R., Yu, D., & Beimborn, E. (2002). Transit user perceptions of the benefits of automatic vehicle location. Transportation research record1791(1), 127-133. doi:10.3141/1791-19



  • Huang, R., & Peng, Z. R. (2002). Object-oriented geographic information system data model for transit trip-planning systems. Transportation research record1804(1), 205-211. doi:10.3141/1804-27



  • Huang, R., & Peng, Z. R. (2002). Schedule-based path-finding algorithms for transit trip-planning systems. Transportation Research Record1783(1), 142-148. doi:10.3141/1783-18



  • Peng, Z. R. (2001). Internet GIS for public participation. Environment and Planning B: Planning and Design28(6), 889-905. doi:10.1068/b2750t



  • Peng, Z.-R., & Beimborn, E. (2001). Breakeven Analysis for Statewide Intelligent Transportation System Project Identification and Assessment. Transportation Research Record1777(1), 105–115. https://doi.org/10.3141/1777-11



  • Peng, Z. R., & Huang, R. (2000). Design and development of interactive trip planning for web-based transit information systems. Transportation Research Part C: Emerging Technologies8(1-6), 409-425. doi:10.1016/S0968-090X(00)00016-4



  • Jan, H. (2000). Peng,“Using GPS Data to Understand Variations in Path Choice”, retrieved on Apr. 15, 2010 at<>, National Research Council. Transportation Research Record1725, 37-44. doi:10.3141/1725-06



  • Wiggins, L., Deuker, K., Ferreira, J., Merry, C., Peng, Z. R., & Spear, B. (2000). Application challenges for geographic information science: Implications for research, education and policy for transportation planning and management. URISA-WASHINGTON DC-12(2), 51-60.



  • Peng, Z.-R. (1999). An Assessment Framework for the Development of Internet GIS. Environment and Planning B: Planning and Design26(1), 117–132. doi:10.1068/b260117



  • Peng, Z. R., & Jan, O. (1999). Assessing means of transit information delivery for advanced public transportation systems. Transportation research record1666(1), 92-100. doi:10.3141/1666-11 (SCI)



  • Peng, Z. R., Groff, J. N., & Dueker, K. J. (1998). An Enterprise GIS database design for agency-wide transit applications. URISA-WASHINGTON DC-10, 46-55.



  • Peng, Z. R., & Nelson, A. C. (1998). Rural transit services: A local economic and fiscal impact analysis. Transportation research record1623(1), 57-62. doi:10.3141/1623-08



  • Peng, Z. R. (1997). A methodology for design of a GIS-based automatic transit traveler information system. Computers, environment and urban systems21(5), 359-372. doi:10.1016/S0198-9715(98)00006-4



  • Peng, Z. R. (1997). The jobs-housing balance and urban commuting. Urban studies34(8), 1215-1235. doi:10.1080/0042098975600



  • Peng, Z. R., Dueker, K. J., Strathman, J., & Hopper, J. (1997). A simultaneous route-level transit patronage model: demand, supply, and inter-route relationship. Transportation24(2), 159-181. doi:10.1023/A:1017951902308



  • Peng, Z. R., & Nebert, D. D. (1997). An Internet-based GIS data access system. URISA-WASHINGTON DC-9, 20-30.



  • Peng, Z., Dueker, K. J., & Strathman, J. G. (1996). Residential location, employment location, and commuter responses to parking charges. Transportation Research Record1556(1), 109-118. doi:10.3141/1556-13



  • Peng, Z., & Dueker, K. J. (1995). Spatial data integration in route-level transit demand modeling. Journal of the Urban and Regional Information Systems Association7(1), 26-37.



  • Peng, Zhong-Ren; & Zhou, Xue-Qing (1989). Paradoxes in the Strategic Research. Sciences, Shanghai, PRC, 40(2). (in Chinese)




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