Search

Objectives: In recent years, the convergence of shield tunnel using the terrestrial laser scanning is more and more widely, but stations changed frequently have an extreme influence on monitoring efficien-cy. The position of endpoints will change with the tunnel deformation when the laser point clouds is applied to fit curve in order to calculate the coordinates of endpoints. Therefore, it is difficult to ensure that the same convergent endpoints are obtained at different times using fitting curve based on point clouds which have an influence on the precision of convergence.Methods: Aiming at the problem of low efficiency of sta-tion-based 3D laser scanning, this paper introduces an economical, efficient and reliable mobile laser scan-ning monitoring method. For the calculation of convergence value, this paper introduces a new method based on tunnel expanded image in detail. Firstly, the expanded images of tunnel were obtained by the cy-lindrical projection of point clouds, the expansion of standard cylinder and gray rasterization, interpolation and gray enhancement of image. Secondly, it can accurately locate the section of point clouds of each ring in shield tunnel through the binaryzation of image, connected analysis, automatic identification and manual correction of ring cracks. Then, the positions between segments of each ring were manually drawn in the expanded image and the orientations of the fixed endpoints were deduced. Finally, the coordinates of the convergent endpoints were calculated and the convergences were calculated by fitting the segments. Re- sults: The results show that the difference between the repetitive results of the convergence value using mo-bile laser scanning is less than 1.5 mm. Conclusions: The proposed calculation method can efficiently moni-tor the convergence of the single-circle shield tunnel with reliable accuracy. [ABSTRACT FROM AUTHOR]

This paper proposed an organization method of laser point cloud data for the efficient management and rapid visualization of the massive point cloud data of vehicle-mounted laser scanner. In this paper, both the original point cloud data and its trajectory are sectioned for the fast indexing firstly, then the LOD(levels of details) index of each section is build based on octree structure. With a tile type and multiresolution storage mode based on folder system, the depth of octree structure is represented by the level of folder directory, and in every node folder, the corresponding point cloud data file and its node properties file are both include. The storage method of this paper decreases the preprocessing time greatly and can support concurrent access owing to mutually independence of each node. Moreover, with the application of view frustum culling technology and multi-thread dynamic dispatch technology, the rendering and roaming of massive point cloud can realize real time updating according to viewpoint change, which significantly improves the dispatch efficiency of vehicle-mounted laser point cloud data. In the experiment, our method was compared with several popular software of point cloud data processing (e.g. XGRT, Quick Terrain Reader) on the data dispatch. The results show our method has obvious advantage on storage capacity, data access time, memory footprint, rendering frame rate and so on, it indicates our method is effective for the management of vehicle-mounted laser point cloud data and can improve the production efficiency for indoor-work of vehicle-mounted laser point cloud data processing. [ABSTRACT FROM AUTHOR]

Mobile mapping technology can be used to acquire geospatial data efficiently, accurately and at low cost, it is one of the most advanced technologies for geospatial data acquisition. A precondition for acquiring high quality point clouds using mobile laser systems is that the mobile system be well calibrated. Ground control points are used in the common method to calibrate mobile laser systems, but these methods as inflexible and it is labor intensive to collect ground control points. In this paper a mobile laser system calibration method using no ground control points is proposed, an actual system was calibrated using the proposed method, and its precision evaluated. [ABSTRACT FROM AUTHOR]

An automatic extraction method of expressway road surface from mobile laser scanning (MLS) data is presented. Through an analysis of the spatial characteristics of expressway MLS point cloud data, an approximate plane constraint (APC) method, an ordering least square method of slope estimation and multi-scale window iterative analysis (MWIA) method were developed to extract initial ground seed points on the grid, and then all road surface points are extracted from the original points based on local slope. Finally, two groups of actual point cloud data were selected for an experiment, the results show that the proposed method can quickly and accurately extract a road surface from MLS data. The correctness of our road extraction results was 95. 74% and completeness was 98. 11%. [ABSTRACT FROM AUTHOR]