As a crime rate denominator, the ambient population has seen very limited use in a multivariate context. The current study employs a new measure of this population, constructed using cell tower location data from OpenCellID, to compare residential and ambient population-based crime rates. The chosen study area is Vancouver, BC, but the conclusions generalize to other administrations and the OpenCellID data have global coverage so the implications are applicable elsewhere. Five disaggregated property crime types are examined at the dissemination area level. Findings demonstrate striking differences in the spatial patterns of crime rates constructed using these two different measures of the population at risk. Multivariate results from spatial error models also highlight the substantial impact that the use of a theoretically informed crime rate denominator can have on pseudo R² values, variable retention, and trends in significant relationships. Implications for theory testing and policy are discussed. In particular, the results suggest that policies designed around residential-based crime rates risk having no effect, or even of increasing crime.

作为犯罪率的分母，环境人口在多变量环境中的使用非常有限。当前的研究采用了这一人口的新措施，使用来自 OpenCellID 的蜂窝塔位置数据构建，以比较基于住宅和周围人口的犯罪率。选择的研究区域是不列颠哥伦比亚省温哥华，但结论可推广到其他主管部门，并且 OpenCellID 数据具有全球覆盖范围，因此其影响适用于其他地方。在传播区域级别检查了五种分类的财产犯罪类型。调查结果表明，使用这两种不同的风险人口衡量指标构建的犯罪率空间模式存在显着差异。R ²值、变量保留和重要关系中的趋势。讨论了对理论测试和政策的影响。特别是，结果表明，围绕基于住宅的犯罪率设计的政策可能没有效果，甚至会增加犯罪率。