QR-tree: a hybrid spatial index structure

In this paper, we present a quick speed spatial indexing structure, which is based on quadtree and R-tree. We name it QR-tree. The research indicates although QR-tree always demands more storage space than R-tree, it gains better performance in insertion, deletion, and especially searching. It also shows that the more amounts of spatial data is, the closer the storage cost of QR-tree and R-tree are and the better performance QR-tree has. In other word, for very large spatial database, QR-tree possesses more superiority than R-tree.