Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data an alysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spat ial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in th is research is that there are substantial inconsistencies in standard choro pleth display options found in two widely used commercial geographical info rmation systems, both in terms of definition and performance. The comparati ve results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial da ta analysis.