Abstract
There is a continuing determination by academics and road professionals alike to investigate the most appropriate methods for identifying road accident hotspots particularly in urban areas. Increasingly this research has involved the use of GIS and spatial analysis in order to define both visually and statistically what can be defined as a road accident hotspot. Traditional methods of hotspot detection by road professionals have included comparing count data at different locations and rating the areas by severity. However the increase use of GIS has lead to academics using sophisticated methods to quantify hotspots. There is, however, no universal definition of a road accident hotspot which means that the definition of a hotspot is open to much speculation. This paper seeks to investigate the merits of three different spatial techniques for quantifying road accident hotspots. Kernel density estimation, network analysis and area wide analysis are used to demonstrate three methods. The methods are then reviewed. There is however an exhaustive list of hotspot detection techniques, not all of which can be outlined in this paper.
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