机载激光扫描测高数据滤波

Airborne laser scanning altimetry data filtering

机载激光扫描测高数据的滤波和分类是获取高精度数字高程模型的关键,也是国际上目前研究的重点和难点之一。本文详细研究了机载激光扫描测高数据滤波的方法,对现有各种滤波算法进行了综合评价,指出了现有方法的不足,在此基础上首次将"移动曲面拟合预测"滤波算法用于机载激光扫描测高数据滤波处理。试验结果表明该算法自适应性强,计算速度快,滤波效果好。通过对不同测区的数据进行实验,给出了滤波前后的对比结果。

airborne laser scanning altimetry data filtering is one of the most important task in Lidar data processing. Filtering is to eliminate of vegetation and building points, generally offterrain points. In this paper refined methods for the restitution of airborne LIDAR data are presented which have been developed based on the rovering conicoid smoothing algorithm. The exiting methods and algorithm are reviewed briefly. And then the proposed algorithm is developed in the next sections. Several typical test sites are used to verify the proposed algorithm. Filtered results are demonstrated one by one. The method, developed in this paper, distinguishes itself in adaptation to the terrain condition. Even in steep terrain ground points and huge building, or dense covers, are classified correctly, offterrain points are eliminated.