基于机载LiDAR数据的建筑物点云提取  

Extraction of buildings based on airborne LiDAR point clouds

作　　者：曹鸿[1] 李永强[1] 牛路标 毛杰[1] 闫阳阳 

机构地区：[1]河南理工大学测绘与国土信息工程学院,河南焦作454000

出　　处：《河南城建学院学报》2014年第1期59-62,76,共5页Journal of Henan University of Urban Construction

基　　金：国家自然科学基金资助项目(41001304);国家十二五科技支撑项目(2012BAH34B00);河南理工大学博士基金资助项目(B2009-33)

摘　　要：LiDAR技术是快速获取地面及地物三维数据的新型测绘技术,也是近年来进行城市三维建模的一种重要手段,而对建筑物的提取是城市三维建模的重要步骤。为了从原始机载点云中有效地提取出城市建模所需要的建筑物点云,在常用机载LiDAR滤波与点云分类思想的基础上,提出了结合面积与斜率两特征参数的区域增长算法,实现了高大植被与建筑物点云的有效分离,完成了建筑物点云的提取。通过设定合理的面积阈值与斜率阈值,结合具体的数据通过该算法获得了较好的提取效果,最后对提取方法及效果进行了客观分析与评价。LiDAR technology is a new mapping technology that has a fast access to the three-dimensional data of ground and surface features, it is also an important means to obtain 3D City Model In recent years, the ex- traction of the building is an important step in the 3D City Model Building. In order to effectively extract build- ings point clouds which are necessary for the City Modeling Building from the original point cloud of airborne Lidar data, by introducing the common airborne LiDAR filtering and classification concept, This article puts forward a region growing algorithm of combining area and slope parameters to separate the buildings from the trees and complete the task of building extraction. Through setting reasonable thresholds of area and slope, this article obtains a better extraction effect, and makes an objective assessment for the method and the effect.

关 键 词：机载LIDAR 滤波 建筑物提取 区域增长 

分 类 号：P23[天文地球—摄影测量与遥感]