Identifying seasonal spatial patterns of crime in a small northern city,Crime Science

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Identifying seasonal spatial patterns of crime in a small northern city
Crime Science ( IF 3.1 ) Pub Date : 2021-10-26 , DOI: 10.1186/s40163-021-00161-w
Ysabel A. Castle ₁ , John M. Kovacs ₁

Affiliation

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.

中文翻译：

识别北方小城市犯罪的季节性空间模式

目标

探索北方小城市的犯罪空间模式，并评估这些模式在不同季节的相似程度。

方法

加拿大安大略省北湾市（人口 50,396 人）五年内（2015 年至 2019 年）经常与犯罪（盗窃、入室盗窃、家庭纠纷、袭击和邻居纠纷）相关的警察服务请求）。使用描述性统计和核密度映射技术进行探索性数据分析。然后使用安德烈森的空间点模式测试（SPPT）来评估每种呼叫类型在两个不同空间尺度（传播区域和人口普查区）的季节模式（春季、夏季、秋季、冬季）之间的相似程度。