A New Approach of R-tree Construction
Shaoxi Li, Depeng Zhao, Kun Bai · 2012
R-tree is a crucial technique for spatial index. However, coverage and overlap produced by traditional methods are big side effects. In order to minimize the overlap and reduce the coverage, this paper proposes a new R-tree construction method based on clustering algorithm which can minimize the overlap and reduce the coverage to a great extent. This method resolves effectively the clustering storage for the adjacent data, and reduces the overlap between spatial nodes. Comparisons and experiments are conducted and performances are evaluated for this method. The results show that this method has high efficiency in querying.