The Spatial Analysis of Crime Statistics and Crime Mapping: Methodological Issues

Crime maps are becoming significant tools in crime and justice. Advances in the areas of information technology, computing and Geographic Information Systems (GIS) have opened new opportunities for the use of (computerized) mapping in crime control and prevention programs. Crime maps are also valuable for the study of the ecology and the locational aspects of crime. Maps enable areas of unusually high or low concentration of crime to be visually identified. Maps are however only pictorial representations of the results of more or less complex spatial data analyses. This paper discusses the methodological problems with the spatial analysis of crime rates. The Poisson distribution is a natural candidate to model this type of data, but it has the problem that the variance is a function of the mean. In addition, rates in areas with small populations are more variable than in areas where populations are large. Moreover, data may exhibit spatial correlation, so a simple Poisson model fails to account for the whole variability in the underlying crime rates. As a consequence, maps based on crude crime rates and probability maps are misleading. A hierarchical model dealing with all these problems is proposed and applied to the regional analysis of firearm homicides in the Eastern Australian states. The analysis addresses the question of whether rural and non-rural areas differ in their associated risks of firearm-related homicide. It is shown that this risk is not associated with the rural character of an area, but with factors relating to social and economic disadvantage, which affect both rural and non-rural regions equally.