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ISPRS Int. J. Geo-Inf. 2016, 5(9), 148; doi:10.3390/ijgi5090148

Evaluating Temporal Analysis Methods Using Residential Burglary Data

Department of Computer Science and Engineering, Blekinge Institute of Technology, SE-371 79 Karlskrona, Sweden
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Academic Editor: Wolfgang Kainz
Received: 5 July 2016 / Revised: 9 August 2016 / Accepted: 19 August 2016 / Published: 25 August 2016
(This article belongs to the Special Issue Frontiers in Spatial and Spatiotemporal Crime Analytics)
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Abstract

Law enforcement agencies, as well as researchers rely on temporal analysis methods in many crime analyses, e.g., spatio-temporal analyses. A number of temporal analysis methods are being used, but a structured comparison in different configurations is yet to be done. This study aims to fill this research gap by comparing the accuracy of five existing, and one novel, temporal analysis methods in approximating offense times for residential burglaries that often lack precise time information. The temporal analysis methods are evaluated in eight different configurations with varying temporal resolution, as well as the amount of data (number of crimes) available during analysis. A dataset of all Swedish residential burglaries reported between 2010 and 2014 is used (N = 103,029). From that dataset, a subset of burglaries with known precise offense times is used for evaluation. The accuracy of the temporal analysis methods in approximating the distribution of burglaries with known precise offense times is investigated. The aoristic and the novel aoristic e x t method perform significantly better than three of the traditional methods. Experiments show that the novel aoristic e x t method was most suitable for estimating crime frequencies in the day-of-the-year temporal resolution when reduced numbers of crimes were available during analysis. In the other configurations investigated, the aoristic method showed the best results. The results also show the potential from temporal analysis methods in approximating the temporal distributions of residential burglaries in situations when limited data are available. View Full-Text
Keywords: temporal analysis; aoristic analysis; crime analysis; residential burglaries temporal analysis; aoristic analysis; crime analysis; residential burglaries
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Boldt, M.; Borg, A. Evaluating Temporal Analysis Methods Using Residential Burglary Data. ISPRS Int. J. Geo-Inf. 2016, 5, 148.

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