Realization of R-tree for GIS on hybrid clustering algorithm^①

来源期刊：中南大学学报(英文版)2005年第5期

论文作者：黄继先 李青松 鲍光淑

文章页码：601 - 605

Key words：R-tree; HCR algorithm; multi-dimension spatial objects, spatial clustering; GIS

Abstract: The characteristic of geographic information system(GIS) spatial data operation is that query is much more frequent than insertion and deletion, and a new hybrid spatial clustering method used to build R-tree for GIS spatial data was proposed in this paper. According to the aggregation of clustering method, R-tree was used to construct rules and specialty of spatial data. HCR-tree was the R-tree built with HCR algorithm. To test the efficiency of HCR algorithm, it was applied not only to the data organization of static R-tree but also to the nodes splitting of dynamic R-tree. The results show that R-tree with HCR has some advantages such as higher searching efficiency, less disk accesses and so on.