A Model of Point Cluster Generalization with Spatial Distribution Features Recognized and Measured

摘要

Following the line generalization, point cluster generalization becomes the second focus in cartographic generalization field, for many objects distribute in random fashion, such as islands lakes and houses etc. Point cluster generalization contains three aspects: quantity selection, structure selection, and single object simplification. Obviously, structure problem is the key and difficulty among the three ones. Preserving the structure information in spatial distribution is the basis of point cluster generalization. In this paper, based on the Delaunay triangulation and Voronoi diagram model, it focuses on the discussion of spatial distribution properties by recognition and measurement. Four characteristic parameters are defined for distribution property description: distribution density of three dimensions, distribution range of two dimensions, distribution axes of one dimension, distribution center of zero dimension. With the aid of Delaunay triangulation and Voronoi diagram, representation and calculation models of above-mentioned parameters are established.