Abstract

Statistical analyses of urban environments have been recently improved through publicly available high resolution data and mapping technologies that have been adopted across industries. These technologies allow us to create metrics to empirically investigate urban design principles of the past half-century. Philadelphia is an interesting case study for this work, with its rapid urban development and population increase in the last decade. We outline a data analysis pipeline for exploring the association between safety and local neighborhood features such as population, economic health, and the built environment. As a particular example of our analysis pipeline, we focus on quantitative measures of the built environment that serve as proxies for vibrancy: the amount of human activity in a local area. Historically, vibrancy has been very challenging to measure empirically. Measures based on land use zoning are not an adequate description of local vibrancy and so we construct a database and set of measures of business activity in each neighborhood. We employ several matching analyses to explore the relationship between neighborhood vibrancy and safety, such as comparing high crime versus low crime locations within the same neighborhood. We find that neighborhoods with more vacancy are associated with higher crime but within neighborhoods, crimes tend not to be located near vacant properties. We also find that longer term residential ownership in a local area is associated with lower levels of crime. In addition, we find that more crimes tend to occur near business locations but businesses that are active (open) for longer periods are associated with fewer crimes. As additional sources of urban data become available, our analysis pipeline can serve as the template for further investigations into the relationships between safety, economic factors, and the built environment at the local neighborhood level.

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