GIS-Based Spatial Data Query And Management Technology

Due to the volumes and complexity of spatial data, the efficiency of spatial query has been a bottleneck of geographic information system, so the study on spatial data query and management technology has great significance.This dissertation first introduces spatial data types and characteristics, and describes spatial data structure and models. Also, the spatial database technology is discussed. For improving speed of the spatial data query, this thesis also has done some research work on spatial index,algorithm for query processing and cost model technology which are used for optimizing spatial query. Taking notice of the disadvantages and the data structures, algorithms of existing spatial indexes, the thesis mainly introduces a spatial index structure which is based on quadtree and R-tree. According to clustering speciality of R-tree nodes, the more compact and higer clustering performance nodes are, the higher query efficency R-tree has. In this paper, spatial clustering technology has been applied to R-tree, a mixed clustering algorithm based on R-tree, which improve the efficiency of spatial index, is given, and a mixed spatial index of quadtree and clustering R-tree is also given. The method partitions research zone to several some area, and every area based on R-tree. It greatly saves storage space and decreases time of index operation.Based on the MSIQCR, the system"ForMax"is implemented. The system performance is evaluated next.