The Geography of Criminality: Information and GIS Models for Decision Support

Over the last few years a new worldwide socio-economical order lead to an increasing number on crime rates and raised the need to find new ways to handle information about criminality. To better understand its causes, local, regional and national security authorities turned to new decision support tools such as Geographic Information Systems (GIS) and other information technologies to find better solutions. To understand the magnitude of all the variables involved it is necessary to spatially capture and correlate them. Only by doing that it's possible to quantify and qualify some hidden aspects of the phenomena. The city of Lisbon with is new proposed administrative division, reducing from 53 to 24 "freguesias" (minimum administrative division and similar to parish's) implies an enormous degree of uncertainty in the observation and location of criminal data. As the crime is not treated with an exact point, but at the level of parish, it implies that larger parishes are treated by the average crime regardless of place of occurrence. This research combines statistical methods (cluster analysis) and spatial models created with GIS, based on police crime reports. It also details a framework for short-term tactical deployment of police resources in which the objective is the identification of areas where the crime levels are high (enough) to enable accurate predictive models as well as to produce rigorous thematic maps. In recent years police services have engaged on proactive and Intelligence-Led Policing (ILP) methods. This advance was coincident with the recognition of law-enforcement solutions at local level. This paper also engages an approach to ILP as a methodology to provide the necessary tools for Decision Support System DSS) of police departments.