Automatic identification of urban settlement boundaries for multiple representation databases

Intuitive and meaningful interpretation of geographical phenomena requires their representation at multiple levels of detail. This is due to the scale dependent nature of their properties. Considerable interest remains in capturing once geographical information at the fine scale, and from this, automatically deriving information at various levels of detail and scale via the process of generalisation. Prior to the cartographic portrayal of that information, model generalisation is required in order to derive higher order phenomena associated with the smaller scales. This paper presents a technique for automatically identifying settlement boundaries based on our understanding of what constitutes ‘citiness’. From this, partonomic structures can be created that link the broad settlement with its constituent parts. The benefits of the resultant system include the automated populating of multiple representation databases (MRDB), better spatial analysis and the creation of semantic reference systems capable of supporting intelligent query or zoom. The creation of such hierarchical partonomic structures provides a very useful framework within which generalisation can take place. The methodology and implementation are presented together with an evaluation of the results. Future developments are proposed.