3D building change detection by combining LiDAR point clouds and aerial imagery

As the elevation information is not considered in the traditional building change detection methods, this paper presents an algorithm of combining LiDAR data and aerial imagery for the 3D building change detection. With the proposed method, we can extract both the elevation change information and the area change information of the buildings at the same time. Firstly, two DSMs are generated using two periods of LiDAR data. Secondly, differencing, filtering and morphological operations are performed to get the changed DSM area, which is then projected onto the aerial images according to the collinearity equations. After that, the interference of the pseudo-changing areas such as trees is removed using spectrum and texture information of aerial image. Finally, the value of elevation changes and area changes are calculated. Experimental results show that the proposed algorithm can extract the change information of the elevation and area quantitatively, which can provide more comprehensive and accurate information for the building change detection. ©, 2015, Wuhan University. All right reserved.