Visualising the Spatio-temporal Patterns of Motor Vehicle Theft in Adelaide, South Australia

Motor Vehicle Theft (MVT) in Australia is as a serious problem with high social and economic costs. MVT is neither unique nor random, but rather tends to be unevenly distributed and has a spatial-temporal pattern. This study assesses and explains the spatio-temporal distribution of MVT within metropolitan Adelaide based on MVT incidences that occurred in 1999. In this exploratory spatial data analysis of MVT we identify vehicle theft hotspots based on point pattern analysis, determine the changes in spatial distribution of MVT during the day, day of week and time of the year, and investigate the relationship between the location and theft and recovery of motor vehicles in the study area. This study uses Crime Pattern Analysis (CPA) techniques including Kernel Density Estimation and Linkage Analysis to identify patterns in point-based MVT data and discusses the results in terms of crime place theories. Advanced spatial data visualisation techniques such as 3D images and spatio-temporal animation are employed to assist interpretation of crime patterns.