摘要
分析了基于常规QR-树建立空间数据索引的数据结构,常规四叉树在数据量特别大时,导致其QR-树深度特别深,占用空间大,查询效率低,并且平面区域分割极限的确定很不灵活。提出了一种改进QR-的数据模型来建立高效的空间数据索引,通过检测水平和垂直相交区域以确定图元所属节点,从而实现海量数据的快速检索。
It analyzes date structure that establishes spatial date index on the basis of general QR-tree. As data of QR-tree is great, which creates the depth of QR-deeper, more store space and lower efficiency of search, confirmation of the limit of plane region segmentation is not fairly flexible. Based on it, the author puts forward the date model improving QR-to establish effective spatial date index, and the method makes certain map element through checking intersecting aea at horizontal area, and vertical area, to realize quick index of multitudinous dates.
出处
《黑龙江工程学院学报》
CAS
2005年第3期18-20,共3页
Journal of Heilongjiang Institute of Technology
基金
黑龙江省教育厅资助项目(1054177)