Spatial Index Method Based on QCR-tree

The depth of QR-tree and the overlapping areas of directory rectangles of R-tree will increase when the massive spatial data is processed by the QR-tree,which incures lower query efficiency.Aiming at this problem,this paper carries out clustering analysis of index objects by K-means algorithm,and a novel formula of clustering center is constructed to make K-means deal with index objects with various forms.It introduces super nodes for storing the clustering results and proposes a QCR-tree spatial index structure to improve the query efficiency.The insertion,deletion and query algorithms of QCR-tree are presented.Experimental results show that QCR-tree,whose query performance is higher than QR-tree,is fit for processing the massive data.