LiDAR数据中建筑物提取的新方法-Fc-S法

激光雷达技术(LiDAR)已广泛应用于数字高程模型(DEM)的快速获取和三维城市模型的建立中,但仍有许多不足之处,需要做更深入的研究。本文介绍了一种新的建筑物提取方法,称之为Fc-S法。该方法首先利用等高线特征进行滤波,从LIDAR数据内插的数字表面模型(DSM)中提取出DEM,利用DSM与DEM的高差阈值和DSM边缘特征参数去掉地面点和汽车等矮小物体,获得主要包含植被和建筑物的地物点群,然后对地物点群进行分割,利用二次梯度和面积等参数去掉植被点,并采用迭代逼近的方法精化建筑物。文章通过实验对所提方法进行验证,并借助高分辨率的航空影像对建筑物提取结果进行评估,评估结果表明该方法能够在地形起伏的区域中较准确地提取出建筑物。

Fc-S method for extracting buildings from LIDAR data

Although LiDAR data is widely used in digital terrain model (DEM) and 3-D building extraction,those extracting methods are still insufficient and need more research.This paper proposed an approach for extracting buildings from LiDAR data,namely Fc-S method.Firstly,it extracted DEM from digital surface model (DSM) interpolated from LiDAR data,and the ground information and low objects,e.g.cars,were removed and object points,mainly included buildings and vegetation were remained using the height difference between DSM and DEM and the feature of edges in DSM.Secondly,the vegetation was discarded from object points using the parameters of the quadratic gradient and area.Then,the fine buildings were extracted with iteration technique.The extracted buildings were evaluted by comparing with the high-resolution areial photograph acquired in the same area finally.The results showed that the proposed method could extract buildings relatively accurate in the regions with undulatory surface.