Vehicle Crime: Communicating Spatial and Temporal Patterns
By Shane D Johnson, Lucía Summers and Ken Pease
Previous research by the writers and others demonstrated clustering of domestic burglary in space and time. This enabled the development of a predictive mapping instrument (PROMAP) which substantially outperforms traditional crime mapping in anticipating burglaries. This report seeks to determine whether the clustering which underpins PROMAP is also evident in relation to vehicle crime, specifically Theft from Motor Vehicle (TFMV) and Theft of Motor Vehicle (TOMV). Data of recorded vehicle crime over a one year period from Derbyshire and Dorset were examined to test that proposition. Analyses demonstrated that • TFMV clusters closely in space and time in both police force areas. When such an offence occurs at one location another is likely to occur nearby and soon after. To use the vocabulary of an epidemiologist, like burglary the risk of this type of vehicle crime is highly communicable. • TOMV clusters somewhat, but not in the same way or with the same closeness as TFMV. The pattern is similar in both force areas. • The spatio-temporal signatures of the two types of vehicle crime, as noted above, differ.This suggests different targeting or foraging strategies are employed for these two types of crime. The difference is consistent with common sense, since there is more post-offence activity implied in theft of a car (onward selling, changed identity, enjoying performance for a non-trivial period) than for theft from a motor vehicle, where the primary constraint on further offending is the offender’s carrying capacity. • There are data limitations which have implications for the ease with which a PROMAP variant dealing with vehicle crime could be deployed operationally. These include shortcomings in the current recording of locations of vehicle crime, and the special problems in mapping crime in car parks, Notwithstanding current data limitations, the patterning of vehicle crime in time and space is such as to encourage the view that prospective mapping could, with proper implementation, prove operationally useful in crime reduction and offender detection
London: UCL, Jill Dando Institute of Crime Science, 2006. 52p.