Agglomerative Effects of Crime Attractors and Generators on Street Robbery? An Assessment by Luojia 1-01 Satellite Nightlight

多级模型 计量经济学 层次聚类 负二项分布 吸引子 地理 统计 犯罪学 计算机科学 数学 社会学 聚类分析 泊松分布 数学分析
作者
Lin Liu,Hanlin Zhou,Minxuan Lan
出处
期刊:Annals of the American Association of Geographers [Taylor & Francis]
卷期号:112 (2): 350-367 被引量:11
标识
DOI:10.1080/24694452.2021.1933888
摘要

Scholars have long confirmed the agglomerative effect in retail geography. The colocation of multiple shops would encourage customers to make multiple stops in a single shopping trip. Does the agglomerative effect exist in illegal activities such as crime? What is a viable measurement of the colocation of facilities that attract or generate crime? These questions have never been explicitly addressed in crime geography. Numerous studies explain crime by the count of facilities, but the count variable ignores the size variation among the facilities. Because facilities are typically associated with lights at night, this study uses Luojia 1-01 satellite nightlight and a Gini coefficient–based adjuster to infer the agglomerative impact of crime attractors and generators in Cincinnati, Ohio. Results show that nightlights have a strong spatial correlation with the facilities and they can effectively capture large-sized and moderate-sized clusters of diverse types of crime attractors and generators. Additionally, negative binomial regression models compare the impacts of these different measures on crime by controlling potential confounding variables representing social disorganization. Results show that the nightlight models outperform the count models. Such advantage is more pronounced in areas where the crime rates are high. This is certainly an encouraging outcome, because both crime research and crime prevention tend to focus on high-crime areas. In sum, this preliminary study on the possible agglomerative effect in illegal activities reveals that nightlight data can effectively measure the agglomeration of crime attractors and generators and that the agglomerative nightlight explains crime better than the popular measure of facility counts.
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