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

YU Anbin; MEI Wensheng

doi:10.13203/j.whugis20170419

Volume 44 Issue 10

Oct. 2019

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Geomatics and Information Science of Wuhan University > 2019 > 44(10): 1553-1559. > DOI: 10.13203/j.whugis20170419

YU Anbin, MEI Wensheng. An Efficient Management Method for Massive Point Cloud Data of Metro Tunnel Based on R-tree and Grid[J]. Geomatics and Information Science of Wuhan University, 2019, 44(10): 1553-1559. DOI: 10.13203/j.whugis20170419

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

YU Anbin^{1, 2,},
MEI Wensheng^{1, 2, ,}

1.
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
2.
Key Laboratory of Precise Engineering and Industry Surveying, National Administration of Surveying, Mapping and Geoinformation, Wuhan 430079, China

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Author Bio:
YU Anbin, PhD, specializes in the theories and methods of underground engineering surveying and data processing.E-mail:972484959@qq.com
Corresponding author:
MEI Wensheng, PhD, professor. E-mail:wshmei@sgg.whu.edu.cn
Received Date: November 28, 2018
Published Date: October 04, 2019

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Abstract

Abstract

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.
- metro tunnel,
- massive point cloud management,
- hybrid index,
- point cloud data,
- R-tree,
- grid

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

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