Abstract
With the development of GIS, it is in great need of integration of multi-source heterogeneous spatial data at different scales. Most of the existing scale generalization algorithms aim at particular types of geo-spatial objects, which are short of versatility. Based on the functional classification and the definition of multi-scale generalization operators, a general multi-scale conceptual model is proposed for various geo-spatial elements, which is expressed in the form of data-operator-relation triple. A corresponding Agent model and a processing flow are also designed for automatic generalization. Through an example, the conceptual model is verified to be adaptive for different kinds of geo-spatial elements. And the Agent-based multi-scale generalization method is effective and fully automatic.
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