Indexing of Constrained Moving Objects for Current and Near Future Positions in GIS

In geographic information system (GIS), fast and efficiently indexing moving objects are a crucial issue in several application domains, such as LBS, intelligence transportation and digital battle. In this paper, a new index structure, PQR-tree, is proposed to fast update and efficiently index the present or near future positions of constrained moving objects based on the characters of moving objects. PQR-tree is an integrated tree structure which combined PMR quadtree, quadtree and R*-tree together. Firstly, QR-tree which combined quadtree and R*-tree is used to carry out rough level partition for index space based on range region. Next, an R*-tree is used to index quasi-static objects for each subspace. Then, using a splitting rule of PMR quadtree to carry further level partition for index space based on road networks and all fast moving objects are related to the road networks. The experimental results show that PQR-tree achieves better performance for index updating and query evaluation than TPR-tree