Research And Implement Of Spatial Data Index Technology Based On R-Tree

In recent years, the Geographic Information System(GIS)has made great progress and has been widely used in public administration, scientific research, business and related fields of people's daily life. It plays a more important role to store, access, express and evaluate massive spatial data in the geographic information system. Traditional relational database can store the spatial data, but it does not support the access efficiently. This is because the multi-dimensional characteristics of spatial data can not adapt to the normal index of relational databases, which leads to the introduction of spatial index.The index and query of spatial data plays an important part in the key research problems of spatial databases. The performance of query determines the performance of spatial databases because that query is the primary operation in databases. Moreover, a good index mechanism also determines high performance of query. Establishing a index mechanism with high performance is the most important thing to spatial databases with a large number of data.This paper starts from the introduction of classic spatial database index technology. Firstly, the basic principles and its ralated major methods of different spatial database index technology are described. Then analyze the advantages and disadvantages of the main design idea of a variety of spatial database indexing technology. Then the paper analyzed its method of optimization for R-tree index.Secondly, based on the research and discussion of classic R*-tree, this paper proposes an improved spatial data index structure called R0-tree, and gives correlation algorithm. The main idea is to store outlier objects in internal tree nodes. If such objects are stored at higher levels of the tree, the lower-level nodes have smaller minimum bounding rectangles and thus the index performs of spatial data is better. Finally, the performance comparision between the R0-tree index and R*- tree index is got by testing a large number of real spatial database test data sets. Test results show that, R0-tree index can improve utilization of space efficient, and also can reduce the number of disk I/Os , so that the performance index can be increased significantly.