机载LiDAR数据提取山区道路方法研究

Road Extraction Using Airborne LiDAR Data in Mountainous Areas

结合山区道路的空间分布特点和激光点云特征,提出了一种从机载LiDAR数据中快速提取山区道路的方法。首先,利用形态学滤波方法进行点云滤波,以去除原始数据的非地面点(建筑、输电线路以及植被等)。在此基础上,采用基于多规则区域生长算法提取道路点并进行优化、然后采用Freeman链编码方法定位追踪道路边界,并利用数学形态学方法进一步细化道路中心线,进而提取完整的道路信息。利用山区机载LiDAR点云数据进行试验并与其他方法的处理结果进行比较,结果表明:本文方法能够有效地从激光点云中提取道路信息:提取道路的完整度为93.87%,正确率为93.84%,质量为88.43%。

Based on the spatial distribution and characteristics of LiDAR points cloud of roads in mountainous areas,an effective method for road extraction from airborne LiDAR data is proposed in this research.First,the morphological filtering method is applied to remove above-ground points cloud（such as buildings,transmission lines and vegetation etc.）.Second,a region growing algorithm with multiple rules is used to extract and optimize the road points cloud.Finally,the road boundaries are located and tracked by using Freeman chain code method.Moreover,the mathematical morphology refining processing is used to extract the central line of mountainous road.The experimental results show that the proposed method is effective to extract road information in mountainous areas,and the completeness,accuracy and quality are 93.87%,93.84%,88.43%,respectively.