一种改进的真三维R树空间索引方法

基金项目: 国家973计划资助项目(2004CB318206);湖北省青年杰出人才基金资助项目(2004ABB018);数字志莲净苑木构佛寺演示系统资助项目

详细信息

An Improved Full 3D R-Tree Spatial Index Method

¹ State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,129 Luoyu Road,Wuhan 430079,China;² School of Geography and Environment,Jiangxi Normal University,99 Ziyang Road,Nanchang 330022,China

Funds: 国家973计划资助项目(2004CB318206);湖北省青年杰出人才基金资助项目(2004ABB018);数字志莲净苑木构佛寺演示系统资助项目

摘要: 利用k-均值算法和覆盖体积与重叠体积之和作为分组的综合指标,改进了现有的三维空间聚簇分组和R树插入算法。实验证明,该算法显著减少了R树兄弟节点之间的重叠现象,而且节点尺寸均匀,有利于海量三维空间数据的高效管理与实时可视化应用。
- 真三维空间索引 /
- R树 /
- 空间聚簇分组 /
- 多细节层次
Abstract: Aiming at the integrated representation of aboveground and underground,indoor and outdoor objects,full 3D spatial index is urgently required.Existing R-tree methods are usually limited by their disadvantages such as the critical overlay of sibling nodes and the uneven sizes of nodes.In order to solve this problem,k-even algorithm is introduced and the sum of overlap and overlay volume is employed as the grouping criterion,which improve the spatial cluster grouping and R-tree insertion algorithms,and therefore evidently reduce the overlap of R-tree sibling nodes and even the size of nodes.
- full 3D spatial index /
- R-Tree /
- spatial cluster grouping /
- LOD