基于激光点云直接比较算法的边坡变形监测技术研究

doi:10.13722/j.cnki.jrme.2014.0584

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Abstract Comparison of point cloud data in different stages is a problem to be solved in slope deformation monitoring by 3D terrestrial laser scanning technology. Through the improvement of Hausdorff distance algorithm，direct precise comparison algorithm based on octree structure is presented. By this means，automatic comparison of multiple point cloud data in deformation region is achieved，reducing manual intervention and improving the efficiency of point cloud data processing. 3D visual laser point cloud data processing and analysis software LPCP is developed on the basis of block management/storage method by octree structure and the theory mentioned above. Application in the deformation monitoring and analysis of Yanjiagou landslide shows that，the caculated deformation region and displacement by this method is accurate in verified with the fixed point monitoring data，DEM analysis results and laser point cloud data of typical section. Moreover，the algorithm is efficient. The method can be extended to a variety of precise deformation analysis，broadening the application area in deformation monitoring greatly for laser scanning technology.

Key words： slope engineering laser point cloud deformation monitoring improvement Hausdorff distance algorithm the octree structure

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https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2014.0584 OR https://rockmech.whrsm.ac.cn/EN/Y2015/V34/Is1/3281

[1] GIRARDEAU-MONTAUT D，ROUX M，MARC R，et al. Change detection on points cloud data acquired with a ground laser scanner[J]. International Archives of Photogrammetry，Remote Sensing and Spatial Information Sciences，2005，36(3)：19. [2] MILLER P，MILLS J，EDWARDS S，et al. A robust surface matching technique for coastal geohazard assessment and management[J]. ISPRS Journal of Photogrammetry and Remote Sensing，2008，63(5)：529–542. [3] ARAV R，FILIN S. Detection and quantification of morphological changes using multi-resolution terrestrial laser scans[J]. ISPRS Annals of Photogrammetry，Remote Sensing and Spatial Information Sciences，2012，(1)：197–202. [4] LAGUE D，BRODU N，LEROUX J. Accurate 3D comparison of complex topography with terrestrial laser scanner：Application to the Rangitikei Canyon(NZ)[J]. ISPRS Journal of Photogrammetry and Remote Sensing，2013，82：10–26. [5] CIGNONI P，ROCCHINI C，SCOPIGNO R. Metro：measuring error on simplified surfaces[J]. Computer Graphics Forum，1998，17(2)：167–174. [6] ASPERT N，SANTA-CRUZ D，EBRAHIMI T. MESH：measuring error between surfaces using the Hausdorff distance[C]// Proceedings of the IEEE International Conference on Multimedia and Expo. [S. l.]：[s. n.]，2002：705–708. [7] ZEIBAK R，FILIN S. Change detection via terrestrial laser scanning[J]. International Archives of Photogrammetry and Remote Sensing，2007，36：430–435. [8] SCHURCH P，DENSMORE A L，ROSSER N J，et al. Detection of surface change in complex topography using terrestrial laser scanning: application to the Illgraben debris-flow channel[J]. Earth Surface Processes and Landforms，2011，36(14)：1 847–1 859. [9] 刘昌军，丁留谦，孙东亚. 基于激光点云数据的岩体结构面全自动模糊群聚分析及几何信息获取[J]. 岩石力学与工程学报，2011，30(2)：358–365.(LIU Changjun，DING Liuqian，SUN Dongya. Automatic fuzzy clustering analysis and geometric information acquisition of rock mass discontinuity based on laser point cloud data[J]. Chinese Journal of Rock Mechanics and Engineering，2011，30(2)：358–365.(in Chinese)) [10] 刘昌军，张顺福，丁留谦，等. 基于激光扫描的高边坡危岩体识别及锚固方法研究[J]. 岩石力学与工程学报，2012，31(10)：2 139–2 146. (LIU Changjun，ZHANG Shunfu，DING Liuqian，et al. Identification of unstable rock mass of high slope and study of anchoring method based on laser scanning[J]. Chinese Journal of Rock Mechanics and Engineering，2012，31(10)：2 139–2 146.(in Chinese)) [11] 刘昌军，黄乾，唐瑜，等. 基于FCM的机载LIDAR数据的建筑物和植被分类方法[J]. 中国水利水电科学研究院院报，2013，(3)：189–194.(LIU Changjun，HUANG Qian，TANG Yu，et al. Classification method for construction and vegetable of airborne LIDAR data based on FCM clustering arithmetic[J]. Journal of China Institute of Water Resources and Hydropower Research，2013，(3)：189–194.(in Chinese))