An Efficient Data Management Approach for Large Cybercity Gis

CyberCity facilitates the processes of urban planning, communication system design, control and decision making, tourism, etc. However, the high efficient database management has become a bottleneck of CyberCity applications. This paper proposes an efficient approach to manage the integrated databases of large CyberCity. This approach consists of following three schemes: At first, a special R+_tree index was designed to accelerate spatial retrieving. The spatial index of CyberCity includes three different types of indexes, i.e. 3D object index, DEM index and image index. The whole city is divided into rectangular regions, and geometries are then classified into the regions by the center of the rectangular bounding box of each geometry. We call it a R+_tree index because among the bounding boxes of local regions has no intersection. And among all the leaf nodes of the R+_tree (geometry records) there is no repetition. Secondly, different data compression algorithms are adopted to compress the digital elevation models, 3D vector models and images, such as LZ77 lossless compression algorithm for compression of vector data and JPEG compression algorithms for texture images. Thirdly, in order to communicate with the Oracle8i database, the CyberCity GIS spatial database engine (SDE) is designed. At last, based on the SDE prototype a case study is presented. It is hopeful to satisfy the requirement of real time applications of CyberCity GIS. It is proved to establish the efficient spatial index and to adopt proper compression methods as well as to extend the data retrieve strategy of commercial ORDBMS are significant for large CyberCity GIS.