L. Kulik, M. Duckham, and M. Egenhofer, Ontology-Driven Map Generalization Journal of Visual Languages and Computing 16 (3): 245-267, 2005.
Different users of geospatial information have different requirements of that information. Matching information to users’ requirements demands an understanding of the ontological aspects of geospatial data. In this paper, we present an ontology-driven map generalization algorithm, called DMin, that can be tailored to particular users and users’ tasks. The level of detail in a generated map is automatically adapted by DMin according to the semantics of the features represented. The DMin algorithm is based on a weighting function that has two components: (1) a geometric component that differs from previous approaches to map generalization in that no fixed threshold values are needed to parameterize the generalization process and (2) a semantic component that considers the relevance of map features to the user. The flexibility of DMin is demonstrated using the example of a transportation network.Posted in Recent Publications