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Open AccessArticle

Space–Time Analysis of Vehicle Theft Patterns in Shanghai, China

Department of Urban and Rural Planning, Soochow University, Suzhou 215123, China
Department of Urban Planning, Tongji University, 1239 Siping Rd., Shanghai 200092, China
Shanghai Tongji Urban Planning & Design Institute, 38 Guokang Rd., Shanghai 200092, China
Urban Informatics & Spatial Computing Lab, Department of Informatics, New Jersey Institute of Technology, Newark, NJ 07102, USA
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(9), 357;
Received: 6 June 2018 / Revised: 10 August 2018 / Accepted: 10 August 2018 / Published: 28 August 2018
PDF [1830 KB, uploaded 28 August 2018]


To identify and compare the space–time patterns of vehicle thefts and the effects of associated environmental factors, this paper conducts a case study of the Pudong New Area (PNA), a major urban district in Shanghai, China’s largest city. Geographic information system (GIS)-based analysis indicated that there was a stable pattern of vehicle theft over time. Hotspots of vehicle theft across different time periods were identified. These data provide clues for how law enforcement can prioritize the deployment of limited patrol and investigative resources. Vehicle thefts, especially those of non-motor vehicles, tend to be concentrated in the central-western portion of the PNA, which experienced a dramatic rate of urbanization and has a high concentration of people and vehicles. Important factors contributing to vehicle thefts include a highly mobile and transitory population, a large population density, and high traffic volume. View Full-Text
Keywords: vehicle theft; environmental criminology; human dynamics; space–time analysis; Shanghai vehicle theft; environmental criminology; human dynamics; space–time analysis; Shanghai

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Mao, Y.; Dai, S.; Ding, J.; Zhu, W.; Wang, C.; Ye, X. Space–Time Analysis of Vehicle Theft Patterns in Shanghai, China. ISPRS Int. J. Geo-Inf. 2018, 7, 357.

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