We propose a method for accurate alignment of ground and aerial multi-view stereo (MVS) models. We achieve this goal by reconstructing the surface meshes from MVS point clouds generated by aerial and ground images respectively, and then iteratively removing the gap between them. The key issue is how to establish reliable correspondences between two meshes. To address this issue, we introduce a new set called the skeleton facet set (SFS) to represent the locally smooth part on the mesh, and then compute the transformation matrix by comparing the depths of the facets in SFS between aerial and ground models. Experimental results show that the proposed method is able to yield accurate alignment results and is robust to noise as well.