VISUALISING THE SPATIO-TEMPORAL PATTERNS OF MOTOR VEHICLE THEFT IN ADELAIDE, SOUTH AUSTRALIA

Abstract Motor Vehicle Theft (MVT) in Australia is as a serious problem with high social and economiccosts. MVT is neither unique nor random, but rather tends to be unevenly distributed and has aspatial-temporal pattern. This study assesses and explains the spatio-temporal distribution of MVTwithin metropolitan Adelaide based on MVT incidences that occurred in 1999. In this exploratoryspatial 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 theyear, and investigate the relationship between the location and theft and recovery of motor vehiclesin the study area. This study uses Crime Pattern Analysis (CPA) techniques including KernelDensity Estimation and Linkage Analysis to identify patterns in point-based MVT data anddiscusses the results in terms of crime place theories. Advanced spatial data visualisation techniquessuch as 3D images and spatio-temporal animation are employed to assist interpretation of crimepatterns.