论文部分内容阅读
利用三维地面激光扫描技术进行边坡变形监测亟需解决多期激光点云数据的比较问题。通过对Hausdorff距离算法的改进,提出基于八叉树结构的点云与点云的精细直接比较算法,实现变形区域多个点云数据的自动比较,减少人工干预,大大提高变形区域激光点云处理效率。基于上述理论和八叉树结构的点云分块管理和存储方法,开发三维可视化激光点云数据处理分析软件LPCP。将该软件应用于阎家沟滑坡的变形监测分析中,经过与固定点监测数据、DEM分析成果和典型断面的激光点云数据的对比验证分析,发现采用点云精细比较算法计算得到的变形区域和位移量准确,计算效率较高。该方法可以推广应用于各种变形的精细比较分析,大大拓宽了激光扫描技术在高精度变形监测中的应用范围。
The use of 3D surface laser scanning technology for slope deformation monitoring needs to solve the problem of multi-period laser point cloud data comparison. Through the improvement of the Hausdorff distance algorithm, a precise direct comparison algorithm of point cloud and point cloud based on octree structure is proposed to automatically compare multiple point cloud data in the deformed area, reduce manual intervention and greatly improve the processing of laser point cloud in the deformed area effectiveness. Based on the above theoretical and octree structure point cloud management and storage methods, the development of three-dimensional visual laser point cloud data processing and analysis software LPCP. The software is applied to the deformation monitoring analysis of Yanjiagou landslide. After comparing with the fixed point monitoring data, DEM analysis results and the laser point cloud data of the typical section, it is found that the deformation area calculated by the point cloud fine comparison algorithm And accurate displacement, higher computational efficiency. The method can be widely applied to the comparative analysis of various deformations and greatly widens the application range of laser scanning technology in high-precision deformation monitoring.