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.
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Huang, Jx., Bao, Gs. & Li, Qs. Realization of R-tree for GIS on hybrid clustering algorithm. J Cent. South Univ. Technol. 12, 601–605 (2005). https://doi.org/10.1007/s11771-005-0130-x
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DOI: https://doi.org/10.1007/s11771-005-0130-x