An overlap minimizing spatial index structure

To reduce overlap between brother nodes, a new index structure for spatial data-a QRMO-tree-was proposed by mapping order relationships between spatial data to partition data space and its subspaces according to the distribution of spatial data contained in it. This minimizes overlap among the nodes on the same level of the tree, making the height of the tree as low as possible. It overcomes problems existing in other spatial structures that are based on R-trees or quadtrees. The algorithms for constructing the index structure, node insertion and range query, theorems for the corresponding algorithm's feasibilities and the accuracy and time complexities of the corresponding algorithms were analyzed. Experimental analysis and comparisons of the overlap among middle nodes were made for the new structure. The experiment showed that overlap among the nodes on the same level of the tree is greatly reduced.