机载LiDAR作为一种新型的对地观测技术,由于具有主动性、受天气影响小、不受阴影影响以及对地物间缝隙具有一定的穿透性等特点,目前备受应用者和研究者的广泛关注。它能直接获取高精度的地表三维点云数据(DSM),为等高线的提取提供了新的契机。由于等高线不能穿过房屋及水系区域,传统方法需要采用人工后处理的方法实现等高线在这些区域的编辑和处理,耗时耗力。因此,提出一种基于特征约束LiDAR点云数据等高线提取方法,该方法主要包括3个方面①点云数据的滤波生成DEM点云数据,为等高线的生成提供基础数据;②基于LiDAR点云数据的特征提取,包括水系、房屋等特征;③在特征提取的基础上,实现基于特征约束的TIN三角网的自动生成,并在此基础上,利用张力样条函数法实现高精度提取。较传统摄影测量立体像对方法,此方法具有可靠性高、效率快、作业精度高的特点。
As a new remote sensing technology, LiDAR (Light Detection and Ranging) is getting wide attentions from users and researchers for its outstanding features. LiDAR is less affected by weather and shadow and has a certain degree of penetration to the gap between surface features. It gets high-precision 3D point cloud data of the land surface and provides a new method for contour extraction. Since contours can’t pass through the buildings and the water areas, the traditional methods need a lot of manual works to edit the contours in these areas, which costs much time. Therefore a method which could generate contours automatically based on the feature constraints from LiDAR point clouds is proposed in this paper. This method mainly includes the following aspects (1) DEM generation which provides basic data for the generation of contours; (2) Feature extraction based on LiDAR point data, mainly including buildings and waters, etc. (3) Automatic generation of TIN based on feature extraction, and on this basis, extraction of fine contours by tension spline function. Compared with the traditional technology of photogrammetry and stereopair, the method in this paper is more reliable, efficient and precise.
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