The relationship between street environment and street crime: A case study of Pudong New Area, Shanghai, China

Zeng, Minling; Mao, Yuanyuan; Wang, Can

doi:10.1016/j.cities.2021.103143

Cited by 22 publications

(4 citation statements)

References 33 publications

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“…There is multitudinous literature on criminal activities in the economically prosperous in Eastern China, while less research has examined crimes in poor Western China. For example, Minling Zeng et al studied criminal activity in Pudong New Area, Shanghai, China [ 26 ]. Shanhe Jiang et al explored perceptions of property crime at the neighborhood level in in Guangzhou, China [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Identifying the Spatio-Temporal Characteristics of Crime in Liangshan Prefecture, China

Cheng

Rao

Tang

et al. 2022

IJERPH

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Crime prevention and governance play critical roles in public security management. Liangshan Yi Autonomous Prefecture in Sichuan Province has a high crime rate, and spatio-temporal analysis of crime in this region could assist with public security management. Therefore, Liangshan Prefecture was selected as the research object in this study. The spatial crime data were obtained from China Judgments Online, and property crime, violent crime, and special crime (i.e., pornography, gambling, drugs, and guns) were analyzed. The findings were as follows. In terms of time characteristics (month, day, and hour), property crime tended to occur in autumn and winter, in the early month, on Wednesdays and Fridays, and at early morning. Violent crime tended to occur in winter and spring, on Mondays and Thursdays, and at night. Special crime occurred in spring and autumn, on Tuesdays, and in the daytime. In terms of spatial features, the central region of Liangshan Prefecture was the focal area for crime. There were obvious low-aggregation areas in the western region for special crime. The eastern region exhibited a high incidence of various crimes. Regarding the spatio-temporal evolution characteristics from 2013 to 2019, there were some obvious hotspots of violent and property crime in downtown and surrounding townships of Xichang City, which is the capital of Liangshan Prefecture. During the study period, the incidence of special crime has an obvious downward trend which shows that there are more new cold spots.

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Section: Discussionmentioning

confidence: 99%

Identifying the Spatio-Temporal Characteristics of Crime in Liangshan Prefecture, China

Cheng

Rao

Tang

et al. 2022

IJERPH

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“…It should be noted that environment-related and human-related factors are not independent but correlated with each other, especially with the underlying geographic space. For example, as the skeleton of urban form, the street structure affects, even shapes, the human activities, while human activities are closely related to criminal events [18,19]. Previous studies mainly explored the influence of street structure on crime from a single "network" perspective, focusing on the influence of street permeability on human presence or crime occurrence; because street permeability may increase human presence, and both are closely related to public surveillance and criminal activities [8].…”

Section: Crime Association Analysismentioning

confidence: 99%

“…First, spatial environment is highly correlated with factors in other dimensions, for instance, human mobility. As an important component of spatial environment, the underlying geographic space affects, even shapes, the human activities and urban forms [18,19]. Second, the crime is heterogeneously distributed and the spatial heterogeneity for crime is associated with the multiscale problem.…”

Section: Introductionmentioning

confidence: 99%

Measuring the Influence of Multiscale Geographic Space on the Heterogeneity of Crime Distribution

He,

Wang,

et al. 2023

IJGI

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Urban crimes are not homogeneously distributed but exhibit spatial heterogeneity across a range of spatial scales. Meanwhile, while geographic space shapes human activities, it is also closely related to multiscale characteristics. Previous studies have explored the influence of underlying geographic space on crime occurrence from the mechanistic perspective, treating geographic space as a collection of points or lines, neglecting the multiscale nature of the spatial heterogeneity of crime and underlying geographic space. Therefore, inspired by the recent concept of “living structure” in geographic information science, this study applied a multiscale analysis method to explore the association between underlying geographic space and crime distribution. Firstly, the multiscale heterogeneity is described while simultaneously considering both the statistical and geometrical characteristics. Then, the spatial association rule mining approach is adopted to quantitatively measure the association between crime occurrence and geographic space at multiple scales. Finally, the effectiveness of the proposed methods is evaluated by crime incidents in the city of Philadelphia. Experimental results show that crime heterogeneity is indeed closely related with the spatial scales. It is also proven that the influence of underlying geographic space on crime heterogeneity varies with the spatial scales. This study may enrich the methodology in crime pattern and crime explanation analysis, and it provides useful insights for effective crime prevention.

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“…El miedo a ser víctima de violencia y delitos se han convertido en una de las principales preocupaciones de los ciudadanos en América Latina y el Caribe (Mejia et al, 2014). La delincuencia callejera representa una parte importante de la inseguridad ciudadana (Zeng et al, 2021). Estos actos delictivos ponen en peligro la salud y la vida de las personas (Wang y Ma, 2021), siendo la percepción del miedo al delito un problema de la sociedad actual (Hart, 2017), pudiendo estar presente sin experimentar un delito o delito real (Oh et al, 2019).…”

Section: Introductionunclassified

Análisis de densidad kernel en la zonificación de la percepción de miedo al delito

et al. 2023

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The relationship between street environment and street crime: A case study of Pudong New Area, Shanghai, China

Cited by 22 publications

References 33 publications

Identifying the Spatio-Temporal Characteristics of Crime in Liangshan Prefecture, China

Identifying the Spatio-Temporal Characteristics of Crime in Liangshan Prefecture, China

Measuring the Influence of Multiscale Geographic Space on the Heterogeneity of Crime Distribution

Análisis de densidad kernel en la zonificación de la percepción de miedo al delito

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