Sharon Kazemi and Samsung Lim

1.0 BACKGROUND The problem of deriving a range of map scales from a common database is considered an interesting and challenging area of research and development in today’s map production environment. Technological developments in dynamic cartographic generalisation applications (e.g. mobile mapping, vehicle navigation) call for a robust, practical and cost-effective way of fulfilling automated generalisation needs. The trends toward automated generalisation require a powerful set of software tools to replace traditional methods for cartographic map productions. A review of the literature on automated generalisation implies a need for intensive experiments with the existing tools developed in the industry rather than developing new generalisation systems [Lecordix, 1997; Kazemi, 2003]. Therefore this research has focused on the application of the generalisation tool to the development of a detailed generalisation framework for deriving multi-scale GEODATA. More particularly, the research has focused on utilising the generalisation operators provided by ESRI ArcGISTM, Intergraph DynaGenTM, and Laser-Scan ClarityTM software, combined with the skills of a trained cartographer, to generalise a road network database from GEODATA TOPO-250K Series 2 data and produce smaller scale maps at 1:500,000 and 1:1,000,000.