In July of 2013 a group of undergraduate students from the Federal University of Bahia, Brazil, published a collaborative web map called “Where I Was Robbed”. Their initial efforts in publicizing their web map were restricted to announce it at a local radio as a tool of social interest. In two months the map had almost 10.000 reports, 155 reports per day and people from more the 350 cities had already reported a crime. The present study consists in an investigation about this collaborative web map spatial correlation to official robbery data registered at the Secretary of Public Safety database, for the city of Salvador, Bahia. Kernel density estimator combined with map algebra was used to the investigation. Spatial correlations with official robbery data for the city of Salvador were not found initially, but after standardizing collaborative data and mining official registers, both data pointed at very similar areas as the main hot spots for pedestrian robbery. Both areas are located at two of the most economical active areas of the city, although web map crimes reports were more concentrated in an area with higher income population. This results and discussions indicates that this collaborative application is been used mainly by mid class and upper class parcel of the city population, but can still provide significant information on public safety priority areas. Therefore, extended divulgation, on local papers, radio and TV, of the collaborative crime map application and partnership with official agencies are strongly recommended.

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OBJECTIVETo carry out a spatial analysis of the occurrence of acts of violence (specifically robberies) in public transportation, identifying the regions of greater incidence, using geostatistics, and possible causes with the aid of a multicriteria analysis in the Geographic Information System.METHODSThe unit of analysis is the traffic analysis zone of the survey named Origem-Destino, carried out in Salvador, state of Bahia, in 2013. The robberies recorded by the Department of Public Security of Bahia in 2013 were located and made compatible with the limits of the traffic analysis zones and, later, associated with the respective centroids. After determining the regions with the highest probability of robbery, we carried out a geographic analysis of the possible causes in the region with the highest robbery potential, considering the factors analyzed using a multicriteria analysis in a Geographic Information System environment.RESULTSThe execution of the two steps of this study allowed us to identify areas corresponding to the greater probability of occurrence of robberies in public transportation. In addition, the three most vulnerable road sections (Estrada da Liberdade, Rua Pero Vaz, and Avenida General San Martin) were identified in these areas. In these sections, the factors that most contribute with the potential for robbery in buses are: F1 - proximity to places that facilitate escape, F3 - great movement of persons, and F2 - absence of policing, respectively.CONCLUSIONSIndicator Kriging (geostatistical estimation) can be used to construct a spatial probability surface, which can be a useful tool for the implementation of public policies. The multicriteria analysis in the Geographic Information System environment allowed us to understand the spatial factors related to the phenomenon under analysis.

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