期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 4
出版社：Copernicus Publications
摘要：Interpretability and usability of clustering results are of fundamental importance. A linear time method for transforming point clusters into polygons is explored. This method automatically translates a point data layer into a space filling layer where clusters are identified as so me of the resulting regions. The method is based on robustly identifying cluster boundaries in point data. The cluster polygonization process analyses the distribution of intra-cluster ed ges and the distribution of inter-cluster edges in Delaunay Triangulations. It approximates shapes of clusters and suggests polygons of clusters. The method can then be applied to display choropleth maps of point data without a reference map or to identify associations in the spatial dimensio n for geographical data mining
