一种改进的真三维R树空间索引方法

An Improved Full 3D R-Tree Spatial Index Method

  • 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。

     

    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.

     

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