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Spatial data are frequently generalized in geographical information processing. At SC-DLO this is particularly the case in generating input data for simulation models. Until now the generalization process has been mainly manual, which is time-consuming and subjective. Practical automated methods of generalizing area objects were investigated. Three methods were compared: the first method is based on the geometry of objects, the second on the attributes of objects, and the third uses a combination of geometry and attributes. The last two methods incorporate procedures for applying specific generalization. To evaluate the effects of the different methods various effect measures were defined.
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