摘要
对于三维GIS来说,建立高效的三维空间数据索引是其关键技术之一。R树索引是近年来应用最广泛的方法之一。本文以覆盖面积和重叠面积之和作为R树结点插入标准,并且引入K均值聚类算法对结点分裂算法进行了改进。另外,对于三维GIS中较大的地物如道路、河流等,实施裁剪策略。从而使R树同层结点间的重叠度显著下降,空间对象的聚簇也更趋合理,有效提高了三维GIS数据库的查询速度。
The establishment of high-performance 3D spatial data index is one of the key technologies in 3D GIS. And R-tree index is one of the most widely used methods in recent years. This paper employs the 3D coverage volume and 3D overlap volume as the R-tree insertion criteria and includes the k-means clustering method to improve the node splitting algorithm. In addition, the larger features such as roads, rivers in three-dimensional GIS can be cut out. So that the overlap of R-tree sibling nodes is minimized drastically, clustering of objects in space becomes more reasonable and the query speed of 3D GIS database is increased effectively.
出处
《测绘科学》
CSCD
北大核心
2010年第1期167-168,共2页
Science of Surveying and Mapping
基金
国家基础科学人才培养基金(0630535)
