The role of land use and walkability in predicting crime patterns: A spatiotemporal analysis of Miami-Dade County neighborhoods, 2007–2015

Christopher Cowen, Eric R. Louderback, Shouraseni S Roy

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

This study investigates the relationship between land use, walkability, and the outcomes of neighborhood crime rates of larceny and aggravated assault. We use a combination of OLS regression models, harmonic analysis of diurnal patterns, and geospatial statistical techniques to examine the spatial patterning of larceny and aggravated assault in 782 Census blocks in Miami-Dade County, Florida with long-term data from 2007 to 2015. The results show that neighborhoods (i.e., Census block clusters) with higher levels of walkability have greater levels of aggravated assault. We also find that the increasing land-use diversity increases both aggravated assault and larceny. Finally, aggravated assault peaks during late night hours, while larceny peaks during daytime hours. Based on the results of our study using conventional and geospatial analyses, routine activity and social disorganization theories of neighborhood crime are partially supported, in that more motivated offenders and potential targets increase crime rates, while increased guardianship and informal social control reduce crime rates. The results of this study have important implications for security experts, law-enforcement agencies, and urban planning policy specialists focused on reducing crime in metropolitan areas. It is also relevant for theoretical frameworks designed to explain and predict temporal and spatial crime patterning.

Original languageEnglish (US)
JournalSecurity Journal
DOIs
StateAccepted/In press - Jan 1 2018

ASJC Scopus subject areas

  • Safety Research
  • Strategy and Management
  • Law

Fingerprint Dive into the research topics of 'The role of land use and walkability in predicting crime patterns: A spatiotemporal analysis of Miami-Dade County neighborhoods, 2007–2015'. Together they form a unique fingerprint.

  • Cite this