A spatial multi-criteria decision analysis framework to reveal vulnerabilities of areas to incidences of street robberies

Abstract

Violence in public spaces is an aspect of society that demands analysis since this affects social and economic well-being. On setting out to explore the incidence of violence in public areas, this paper brings a multi-methodology framework to associate the exploratory analysis of data on street robberies with a geographic information system (GIS) and a multi-criteria decision analysis (MCDA) model. Our GIS-MCDA framework is based on a Dominance-based Rough Set Approach (DRSA) and induces the decision-maker to learn and understand the spatial, social, and demographic data on crime analysis. As a result, the study area was classified into levels of vulnerability. We found that the social interaction features, bus stops and street robberies are spatially and statistically associated. From the socio-demographic perspective, makeshift houses, the number of people who can read and write and the number of inhabitants were highlighted as dimensions to be considered when associated with crime. Finally, preferences in evaluation of areas of vulnerability tend to be pessimistic. Therefore, the multi-methodology framework makes a holistic analysis of such vulnerabilities and contributes to improve knowledge on urban spaces and how this informs detecting vulnerability to crime.