基于改进点云数据的测绘工程地貌信息提取方法研究

Research on Geomorphological Information Extraction Method for Mapping Projects Based on Improved Point Cloud Data

摘要: 由于测绘项目中地貌信息提取的难度和通常测绘手段的测量精度较低，为了提高信息提取的精度，本工作充分利用无人机的轻便灵活和LiDAR的高效、快速、局部穿透的特点，在研究区进行无间隙低空采样，有效克服了传统单点数据采集的缺点。在本文中，我们提供了一种提取地貌信息的点云数据采集技术。为了保证三维激光扫描无人机获取的地表点云数据的准确性，避免滤波过程中因地形坡度突变和植被稀疏而导致的滤波不足或过度的问题，本文提出了一种地表插值和高程增强算法，对点云数据进行局部滤波和区分，得到采样点的全局空间分布。从离散的点云数据中形成浮雕轮廓面，对浮雕信息元素进行分类和识别，实现信息提取。实验结果表明，所设计的方法能够消除非地貌目标的干扰，提高提取精度，对地貌信息特征的解释有良好的效果。

Abstract: Due to the difficulty of extracting geomorphological information in mapping projects and the low measurement accuracy of the usual mapping means, in order to improve the accuracy of infor-mation extraction, this work makes full use of the lightness and flexibility of UAVs and the efficient, fast and localised penetration of LiDAR to carry out gapless low-altitude sampling in the study area, effectively overcoming the shortcomings of traditional single-point data collection. In this paper, we provide a point cloud data acquisition technique for extracting geomorphological information. To ensure the accuracy of the surface point cloud data acquired by the 3D laser scanning UAV and to avoid the problem of under- or over-filtering due to abrupt changes in terrain slope and sparse vegetation during the filtering process, a surface interpolation and elevation enhancement algo-rithm is proposed in this paper to locally filter and differentiate the point cloud data to obtain the global spatial distribution of the sampled points. From the discrete point cloud data, a relief contour surface is formed, and the relief information elements are classified and identified to achieve in-formation extraction. The experimental results show that the designed method can eliminate the interference of non-geomorphic targets, improve the extraction accuracy and have a good effect on the interpretation of geomorphic information features.