一种R树与格网结合的海量地铁隧道点云管理方法

为满足海量地铁隧道点云的高效处理需求，提出了一种R树与格网结合的海量地铁隧道点云管理方法。针对隧道点云的空间分布特点，在全局将大范围点云划分到格网中，并使用R树管理非空网格；在局部使用八叉树与四叉树混合的索引方法管理单个网格内的点云。为了提高点云的渲染效果，提出了基于网格面积的多细节层次结构（levels of detail，LOD）回溯构建方法，并采用高效的单文件存储方式存储点云。实验结果证明了所提出的方法在海量隧道点云的管理和可视化方面优于传统方法。

An Efficient Management Method for Massive Point Cloud Data of Metro Tunnel Based on R-tree and Grid

In order to meet the need of highly efficient processing of metro tunnel point cloud, this paper proposes a hybrid index model which combines the R-tree and grids.In global area, the metro tunnel point cloud is divided into grids which are organized by using R-tree method according to its spatial distribution characteristics. And a hybrid spatial index which combines the quadtree and octree is used to manage the point cloud in one grid. In order to improve the visualization effect of metro tunnel point cloud, we propose a method for constructing levels of cletail structure based on the area of the grids. In addition, single file storage method is used to store point cloud data. Experiments results show that the proposed method has advantages in the management and visualization of massive point cloud effect over traditional methods.