Identifying seasonal spatial patterns of crime in a small northern city

• Published in: Crime science Vol. 10; no. 1; pp. 1 - 20
• Main Authors: Castle, Ysabel A., Kovacs, John M.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 26.10.2021; Springer Nature B.V; BMC
• Subjects: Community and Environmental Psychology; Crime mapping; Criminal statistics; Criminology and Criminal Justice; Data analysis; Kernel density mapping; Law and Criminolgy; Seasonal variations; Seasonality; Signal,Image and Speech Processing; Small city; Spatial analysis; Spatial point pattern test; Systems and Data Security; Canada; North Bay Ontario Canada; Crime mapping; Spatial point pattern test; Kernel density mapping; Small city; Seasonality
• ISSN: 2193-7680; 2193-7680
• DOI: 10.1186/s40163-021-00161-w

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.