Abstract. Shape simplification in map-like representations is used for two reasons: either to abstract from irrelevant detail to reduce a map user's cognitive load, or to simplify information when a map of a smaller scale is derived from a detailed reference map. We present a method for abstracting simplified cartographic representations from more accurate spatial data. First, the employed method of discrete curve evolution developed for simplifying perceptual shape characteristics is explained. Specific problems of applying the method to cartographic data are elaborated. An algorithm is presented, which on the one hand simplifies spatial data up to a degree of abstraction intended by the user; and which on the other hand does not violate local spatial ordering between (elements of) cartographic entities, since local arrangement of entities is assumed to be an important spatial knowledge characteristic. The operation of the implemented method is demonstrated using two different examples of cartographic data.

Abstract. In graphics and language, schematization is an important method to emphasize certain aspects and to deemphasize others. Different disciplines use schematization for different reasons. In cartography, graphic schematization is one aspect of map generalization. In contrast, cognitive science addresses schematization as a method to intentionally emphasize certain aspects of knowledge beyond technical necessity; therefore, the notion of schematic map is proposed to denote maps that employ schematization for cognitive representational reasons. This chapter discusses different views of schematization from cartography, linguistics, and artificial intelligence. Connections to qualitative reasoning in artificial intelligence are drawn. We address human spatial cognition and present examples of task-oriented representations. Finally, multimodality for conveying spatial knowledge and its application in schematic maps are discussed.

No abstract

No abstract