Multi-Criteria Approach with Spatial Analysis and Remote Sensing for Public Security Planning

Abstract

Crime prevention requires planning, the identification of critical places, and allocating resources correctly. In order to ensure crime reduction, the participation of security decision makers is necessary in evaluating criteria that influence crime prevention. The decision maker needs to analyse the best actions to control violence, as well as define where these actions should be allocated. This paper suggests a multi-criteria spatial model associated with remote sensing to identify those areas most vulnerable to homicide and consequently in greatest need of public-policy intervention. The model was applied in a Brazilian neighbourhood, taking into account social, economic and demographic factors, as well as satellite images. We conclude that the spatial analysis approach using multiple criteria is a viable option for mapping crime-vulnerable places, since the areas identified as vulnerable have a similar pattern to official maps showing homicide density. The proposed approach presents some methodological advantages: (1) integration of different approaches; (2) consideration of rasters, excluding the need for polygons; (3) consideration of remote sensing, excluding unnecessary areas from the analysis; (4) little effort is required on the part of the decision maker.

Multicriteria Ranking for the Efficient and Effective Assessment of Police Departments

“…Our methodology relies on recent advances in conditional frontier analysis used with a traditional PROMETHEE methodology for outranking decision units. Some assessments of crime and policing in Pernambuco used statistical, multicriteria, and geospatial tools for ranking, clustering, and classifying units and regions according to the vulnerability to homicides [32][33][34], preference learning [35,36], property crimes [37,38], and investigating the violent behavior in Pernambuco [39]. Despite providing valuable support for policymakers, to the best of our knowledge, ranking regions or police units for public security purposes based on a multicriteria combination of nonparametric robust estimators for technical efficiency with measures for effectiveness of results were not featured in the current literature.…”

Multicriteria Ranking for Police Efficient and Effective Analysis

“…In this paper, we combine the Full Disposal Hull (FDH) [20] directional efficiency measure for policing conditional to crime as an exogenous factor with the PROMETHEE outranking for a complete classification of Pernambuco's municipalities based on the efficiency of each police department in solving three types of crimes violent crimes (CVLI), street robberies (mugging) and carjack (or more generally motor vehicle theft and robbery) using officers as input and based on the effectiveness of reaching Pact for Life state goal on reducing homicides [5,21,22]. Some assessments of crime and policing in Pernambuco has used multicriteria and geospatial tools for ranking, clustering and classifying units and regions according to the vulnerability to homicides [23,24,25], preference learning [26,27], and property crimes [28,29]. Despite providing valuable support for policymakers, to the best of our knowledge, ranking regions or police units for public security purposes based on a multicriteria combination of Nonparametric Robust Estimators for the technical efficiency with measures for effectiveness of results is not featured in the current literature.…”