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Crime in an Affluent City: Applications of Risk Terrain Modeling for Residential and Vehicle Burglary in Coral Gables, Florida, 2004–2016

  • Derek Vildosola
  • Julian Carter
  • Eric R. Louderback
  • Shouraseni Sen RoyEmail author
Article

Abstract

Risk Terrain Modeling (RTM) — an innovative geospatial approach to analyze the locations of high crime areas within cities— was used to analyze criminogenic spaces and identify the riskiest places contributing to vehicle and residential burglary in the city of Coral Gables, Florida from 2004 to 2016. Official crime incident data on residential and vehicle burglary were provided by the Coral Gables Police Department. We investigated the role of environmental predictors of crime by analyzing the effects of the designated riskiest places including alcohol vendors, car dealers, gas stations, bars, secondary/post-secondary schools, grocery stores, and restaurants. We identified risky places and their proximity to the occurrence of residential and vehicle burglary with a regression process using the RTM technique to determine the Relative Risk Values (i.e., weighted risk) that each risk factor had. We examined different temporal designations, including day and night, day of the week, and monthly intervals. Our results indicated that restaurants and grocery stores located in the downtown area and along the US 1 highway were higher risk locations for the occurrence of both types of crime throughout the city. The locations of risky places in the study area were spatially consistent with high crime areas, supporting our main hypothesis. The use of RTM with targeted community policing strategies could move policy from a reactionary approach to more proactive solutions to crime prevention. Concepts drawn from routine activity theory, as well as crime and place perspectives, both receive moderate empirical support for vehicle and residential burglary outcomes.

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Geography and Regional StudiesUniversity of MiamiCoral GablesUSA
  2. 2.Department of SociologyUniversity of MiamiCoral GablesUSA
  3. 3.Center for Computational SciencesUniversity of MiamiCoral GablesUSA

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