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 map generalisation. This research presents a model (database) generalisation approach able to support the derivation of phenomena typically present at 1:250,000 scale mapping directly from a large scale topographic database. Such transformation involves creation of composite objects, such a settlement, forest, hills and ranges, from component objects, such a buildings, trees, streets, and vegetation in the source database. In order to perform this transformation it is important to model the meaning and relationships among source database objects rather than to consider the object in terms of their geometric primitives (points, lines and polygons). The proposed approach involves identification of such relationships and then utilising these relationships to create higher order objects. The utility of the results obtained is demonstrated using spatial analysis techniques and the creation of ‘links’ between objects at different representations needed for MRDBs.

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