摘要
在城区的机载LiDAR点云中一般存在大量打在树木上的点,从点云中提取的树木点可以应用于城区绿化面积和树木参数的估计,以及树木的建模。针对城区环境,本文在综合分析树木点和其他地物空间分布模式的基础上,提出了一种只利用点云的几何性质,结合点云空间分布模式来提取树木点的方法。实验表明,该方法可以取得很高的分类精度,卡帕系数为0.9713。
A large amount of points are located on trees in urban airborne LiDAR point clouds. Tree points extracted from point clouds could be used for the estimation of green area and tree parameters and also modeling of tree. At present, the research of tree points extracting method is limited. Based on a com- prehensive analysis of spatial distribution pattern of tree points and other objects, a tree point extraction scheme for urban environment was proposed in this paper which only employs geometric metrics and incor- porates spatial distribution pattern of point clouds. Experiments proved that this method could achieve high classification accuracy with Kappa coefficient 0. 9713.
出处
《测绘科学》
CSCD
北大核心
2014年第3期52-56,共5页
Science of Surveying and Mapping
基金
973项目(2011CB707001)
自然基金项目(41001308
41071291)
测绘遥感信息工程国家重点实验室专项科研经费
关键词
机载LIDAR
点云分类
树木
空间分布模式
airborne LiDAR
point classification
tree
spatial distribution pattern
