This research focused on the effect of the built environment on Bogotá’s violent crime by using the Risk Terrain Modeling (RTM) technique. The current study used 17 ecological variables, including micro-level data on the spatial distribution of socio-economic strata, and the location of an array of businesses and other features of the landscape. As suggested by the results of this study, the spatial distribution of violent crime in Bogotá is highly correlated with the allocation of socio-economic strata throughout its geography. A statistically valid RTM analysis identified the micro-level risk factors associated with three types of violent crime incidents, namely homicide, assault, and theft incidents. These results suggest that future violent crime incidents are more likely to occur at a reduced number of high-risk micro-places. Moreover, while homicide and assault incidents were more likely to cluster within the poorest areas of the city, theft incidents presented a higher risk of victimization near the city center, where economic activity and suitable targets concentrate. This study offers a unique account regarding the effect of socio-economic segregation on violent crime victimization across Bogotá’s geography and within different socio-economic strata classifications.
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Original Spanish passage: “Estratificación social en Bogotá: de la política pública a la dinámica de la segregación social (Uribe-Mallarino 2008, pg. 150)
As of January 2018.
The results to this study were originally presented in June 2015 at a colloquium organized by the World Bank, to a select number of local stakeholders, including transportation managers, city hall officials and local NGOs in the city of Bogotá.
FIP calculations based on data from the Colombian National Police. All crime data was geo-referenced using the WGS84 reference coordinate system.
Currency exchange rate between Colombian Pesos (COP) and U.S. Dollars (USD) as of August 2017.
Note that 1% of the city’s population lived in non-stratum designated units.
(14 factors * 2 operationalizations * 3 blocks * 2 “half increments”) + (3 factors * 1 operationalization * 3 blocks * 2 “half increments”) = 186 variables.
The cell size was 75 m, similar to RTM, and the search radius was set to 450 m. Thus, assuming the maximum spatial influence used with RTM.
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Giménez-Santana, A., Caplan, J.M. & Drawve, G. Risk Terrain Modeling and Socio-Economic Stratification: Identifying Risky Places for Violent Crime Victimization in Bogotá, Colombia. Eur J Crim Policy Res 24, 417–431 (2018). https://doi.org/10.1007/s10610-018-9374-5
- Risk terrain modeling
- Crime analysis
- Urban segregation