A comparative analysis to forecast apartment burglaries in Vienna, Austria, based on repeat and near repeat victimization

Crime Science

Michael Leitner¹  Philip Glasner¹  Shane D. Johnson² 

[1] Department of Geoinformatics–Z_GIS, University of Salzburg;Jill Dando Institute of Security and Crime Science, University College London;

关键词: Repeats;    Near repeats;    Burglary;    Predictive mapping;    Crime prevention;    Vienna;   

DOI  :  10.1186/s40163-018-0083-7

来源: DOAJ

【 摘 要 】

Abstract In this paper, we introduce two methods to forecast apartment burglaries that are based on repeat and near repeat victimization. While the first approach, the “heuristic method” generates buffer areas around each new apartment burglary, the second approach concentrates on forecasting near repeat chain links. These near repeat chain links are events that follow a near repeat pair of an originating and (near) repeat event that is close in space and in time. We name this approach the “near repeat chain method”. This research analyzes apartment burglaries from November 2013 to November 2016 in Vienna, Austria. The overall research goal is to investigate whether the near repeat chain method shows better prediction efficiencies (using a capture rate and the prediction accuracy index) while producing fewer prediction areas. Results show that the near repeat chain method proves to be the more efficient compared to the heuristic method for all bandwidth combinations analyzed in this research.

【 授权许可】

Unknown