3.8 Article

Identifying seasonal spatial patterns of crime in a small northern city

Journal

CRIME SCIENCE
Volume 10, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s40163-021-00161-w

Keywords

Crime mapping; Seasonality; Small city; Spatial point pattern test; Kernel density mapping

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The study explores the spatial patterns of crime in a small northern city and assesses the degree of similarity in these patterns across seasons. Results indicate that crime calls are more dispersed in the warmer seasons of spring and summer, with increases in hotspot intensity but little overall change in pattern. The SPPT test finds some evidence for seasonal differences in crime patterns across the city, specifically for thefts and break and enters.
Objectives: To explore spatial patterns of crime in a small northern city, and assess the degree of similarity in these patterns across seasons. Methods: Calls for police service frequently associated with crime (theft, break and enter, domestic dispute, assault, and neighbor disputes) were acquired for a five year time span (2015-2019) for the city of North Bay, Ontario, Canada (population 50,396). Exploratory data analysis was conducted using descriptive statistics and a kernel density mapping technique. Andresen's spatial point pattern test (SPPT) was then used to assess the degree of similarity between the seasonal patterns (spring, summer, autumn, winter) for each call type at two different spatial scales (dissemination area and census tract). Results: Exploratory data analysis of crime concentration at street segments showed that calls are generally more dispersed through the city in the warmer seasons of spring and summer. Kernel density mapping also shows increases in the intensity of hotspots at these times, but little overall change in pattern. The SPPT does find some evidence for seasonal differences in crime pattern across the city as a whole, specifically for thefts and break and enters. These differences are focused on the downtown core, as well as the outlying rural areas of the city. Conclusions: For the various crime types examined, preliminary analysis, kernel density mapping, and the SPPT found differences in crime pattern consistent with the routine activities theory.

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