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.