ABSTRACT
Several techniques and algorithms are used in practice for the generation of continuous surface hotspot maps, all of which have different merits. These mainly relate to their ease of use, application to different types of events, visual results and interpretation. Few of these methods help to distinguish a consistent defining threshold that helps the analyst decide when a cluster of crimes can be defined as a ‘hotspot’. This paper will present results of some partnered research that explores a procedure for creating statistically robust hotspot maps. Our methods include the application of point pattern analysis techniques to identify for spatial clustering, spatial dispersion, spatial autocorrelation, and Local Indicators of Spatial Association (LISA statistics), plus review the use of spatial analysis tools to visualise and assist in formatting the design of the crime hotspot map and the definition of hotspot thematic thresholds.
