This paper proposes an alternative way to analyse and visualize vulnerability to crime at micro-places according to the different combinations of contextual elements that characterize them. The study focuses on violent crimes in the urban area of Iztapalapa, Mexico City. The identification of the risky places follows the Risk Terrain Modelling approach including both information on environmental elements and on the socio-demographic characteristics of the neighbourhoods. Cluster analysis is applied to classify and map these places according to the different environmental settings. The paper discusses how the suggested visual representations is a powerful communicative means to complement traditional risk maps that simply classify the areas according to their future crime likelihood. The paper argues that displaying the combination of crime correlates ensures more effective risk governance. The paper also indicates how effective communication and the selection of proper graphical visualization of analytical findings are pivotal for fostering collaboration between crime analysts, law enforcement agencies, and other stakeholders.
- Crime, Risk, Crime Analysis, Crime Forecasting, Vulnerability