基于LiDAR点云数据的城市三维绿量分层测算方法研究

Hierarchical measurement of urban living vegetation volume based on LiDAR point cloud data

三维绿量已成为测度城市绿化水平的重要指标。为有效实现其在城市范围内的应用,文中基于LiDAR点云数据与高分辨率遥感影像数据,将"分隔带"法与边缘特征点提取算法相结合,提出一种分层三维绿量测算方法。首先,对LiDAR点云数据与遥感影像数据预处理,包括拼接、匹配、点云去噪及压缩等,提取城市绿化区点云数据;然后,通过"分隔带"法识别不同类别植被分布区,将植被在林层尺度下分割;其次,采用冠体边缘特征点提取算法,快速构建冠体外廓;最后,应用不规则三角网TIN,对绿化植被分层建模并计算。为验证文中测算结果,选取15个随机点建立样方进行实测,经检验表明所得精度较高,能够满足城市范围内三维绿量测算的需求。

Living vegetation volume has become an important indicator to measure the level of urban greening.In order to apply it effectively to urban area,based on LiDAR point cloud data and high resolution remote sensing image data,this paper combines“separation strip”method with extracting algorithm from edge feature points,and proposes a calculation method for layered living vegetation volume.Firstly,LiDAR point cloud data and high resolution remote sensing image data are pretreated,including stitching,matching,point cloud denoising and compressing etc.and then point cloud data of urban greening area are extracted.Secondly,vegetation is separated under forest dimension after identifying different vegetation distribution areas by“separation strip”method.After that,the outline of crown is constructed rapidly by extracting algorithm from edge feature points of crown.Finally,vegetation is layered,built modeling and calculated using triangulated irregular network.This paper choses 15 random points to set up samples for measurement so as to verify the results.The verification shows that the accuracy of results are high enough to meet the demand of living vegetation volume measurement in urban area.