Abstract
Chinese cities have been undergoing extraordinary changes in many respects during the process of urbanization, which has caused crime patterns to evolve accordingly. This research applies a Bayesian spatiotemporal model to explore and understand the spatiotemporal patterns of crime risk from 2008 to 2017 in Changchun, China. The overall temporal trend of crime risk, the effects of land use covariates, spatial random effects, and area-specific differential trends are estimated through a Bayesian spatiotemporal model fitted using the Integrated Nested Laplace Approximation (INLA). The analytical results show that the regression coefficient for the overall temporal trend of crime risk changed from significantly positive to negative after the land use variables are incorporated into the Bayesian spatiotemporal model. The covariates of road density, commercial and recreational land per capita, residential land per capita, and industrial land per capita are found to be significantly associated with crime risk, which relates to classic theories in environmental criminology. In addition, some areas still exhibit significantly increasing crime risks compared with the general trend even after controlling for the land use covariates and the spatial random effects, which may provide insights for law enforcement and researchers regarding where more attention is required since there may be some unmeasured factors causing higher crime trend in these areas.
Highlights
Published: 22 September 2021During recent decades, most cities in China have been undergoing extraordinary changes in many aspects, such as demographic characteristics, socioeconomic status, land use and building environments, which are often proven to be associated with the spatial pattern of crimes in the urban environment in the literature on environmental criminology [1,2,3]
During the process of urbanization over the years studied, the spatial pattern of crimes in Changchun has experienced an obvious change in the characteristics of more dispersed crime risks in the surrounding areas, the total crime counts, the mean of the crime counts and crime rates across all the precincts present a clearly decreasing trend
The results show that the sign of the overall crime trend changes from significantly positive to significantly negative after the land use covariates are incorporated into the Bayesian model
Summary
Most cities in China have been undergoing extraordinary changes in many aspects, such as demographic characteristics, socioeconomic status, land use and building environments, which are often proven to be associated with the spatial pattern of crimes in the urban environment in the literature on environmental criminology [1,2,3]. The patterns of criminal activities in Chinese cities may evolve along with such intense changes, especially in long-term trends. Due to limited access to crime data, information on changes in the crime pattern in Chinese cities with the accelerating process of urbanization is largely lacking. An increasing number of studies have emerged relating to the spatial and temporal patterns of crimes in Chinese cities as relevant data become available.
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