Tuesday, October 2, 2018

Predicting crime locations

Philip Glasner successfully defended his PhD Thesis “Spatial and temporal analysis of crime and the impact of rhythmic cycles to predict future crime locations: Studies from the city of Vienna, Austria” within the Doctoral College “GIScience” at the University of Salzburg.

Based at the Department of Geoinformatics – Z_GIS and supervised by Prof. Michael Leitner who’s primer affiliation is with Louisiana State University, USA and GIS industry, Philip Glasner developed algorithms and methods to predict where crimes such as burglaries are likely to happen next or again. 

He started from existing methods in predictive crime mapping and advanced methods for series events or near repeat victimization including hotspot techniques utilizing retrospective data. As a result, predictions where crime is more likely to occur based on past patterns of crime could be improved. In particular, repeated and near repeated patterns of street robberies in the city of Vienna were continuously analyzed in order to forecast where street robberies are more likely to occur. In addition, temporally imprecise crime events were reviewed and a new method was discussed to overcome limitations to exclude temporally imprecise data in spatiotemporal pattern analysis such as repeat and near repeat victimization. 

The results of this thesis suggest that there is considerable potential for law enforcement in the city of Vienna to employ concepts of predictive policing to forecast future crime events. Based on the findings, law enforcement agencies can optimize tactical and strategical planning of police resources in combating crime. 

We wish Philip all the best for his future career.

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