以冷龙岭断裂上一处典型地貌点云数据为例，采用最邻近法、距离反比法、不规则三角网法、样条函数法、克里金法等5种插值方法进行遗漏点云插值填充，研究并探讨最合适的插值算法。结果表明，不规则三角网插值法不仅可以很好地填充点云遗漏数据，还可以按照实际地形变化精确表示其高程数据并还原野外的真实场景，为后期的研究提供数据保证。"/>
Comparative Study of Point Cloud Data Interpolation Based on Ground-Based LiDAR" />
Taking typical geomorphologic point cloud data on Lenglongling fault as an example, this paper uses five interpolation methods such as nearest neighbor, inverse distance weighting, triangulated irregular network, spline and Kriging, to fill the missing point cloud interpolation. The most suitable interpolation algorithm is discussed. Experiments show that the triangulated irregular network interpolation method not only fills the missing data of point clouds, but also accurately represents the elevation data according to actual topographic changes. This restores the real scene in the field, providing technical guidance and data guarantee for future research."/>
<div style="line-height: 150%">Comparative Study of Point Cloud Data Interpolation Based on Ground-Based LiDAR</div>
Abstract Taking typical geomorphologic point cloud data on Lenglongling fault as an example, this paper uses five interpolation methods such as nearest neighbor, inverse distance weighting, triangulated irregular network, spline and Kriging, to fill the missing point cloud interpolation. The most suitable interpolation algorithm is discussed. Experiments show that the triangulated irregular network interpolation method not only fills the missing data of point clouds, but also accurately represents the elevation data according to actual topographic changes. This restores the real scene in the field, providing technical guidance and data guarantee for future research.
