A Multiscale Assessment of the Impact of Perceived Safety from Street View Imagery on Street Crime

Hanlin Zhou, Lin Liu, Jue Wang, Kathi Wilson, Minxuan Lan and Xin Gu

Annals of the American Association of Geographers, 2024, vol. 114, issue 1, 69-90

Abstract: Perceived safety of the built environment—a cognitive assessment different from emotional fear of crime—might affect the number of potential crime victims in an area and thus affect crime opportunities. The perceived safety derived from street view imagery has propelled scholars to examine its relationship with crime. The literature, however, has not addressed the related geographic scale variability issue; that is, the choice of the geographic analytical units might affect the relationship between area-based perceived safety and crime. This study explores how the relationships between street-view-derived perceived safety and both street thefts and street robberies vary by different spatial scales in Cincinnati. Results of negative binomial models show that perceived safety is positively associated with street thefts and street robberies at both the street segment and census block levels, but is negatively associated with these crimes at the census block group level. The relationship is not statistically significant at the census tract level. This variability is explained by the different freedom of avoidance behaviors in response to perceived safety, which change by geographic scale. The research further evaluates the within variance and between variance of perceived safety at different scales. Compared to between variance, within variance is smaller at both the street segment and block levels, but larger at both the block group and tract levels. This variability can be a source of model instability across multiple geographical scales. In short, the multiscale assessment shows that larger spatial units like the census tract are unsuitable for perceived safety–crime analysis.

Date: 2024
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DOI: 10.1080/24694452.2023.2249975

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