A new method for multisource DEM matching

Digital elevation model (DEM) matching is a necessary task that must be conducted in many applications of remote sensing, especially for purposes of disaster surveillance (e.g., landslide, debris flow). In this paper, we propose a robust matching method based on contour lines and least squares surface matching. Challenges involve detecting stable and invariant control points (CPs) in un-deformed areas in varying situations and complex topographies. We utilize a shape context descriptor to compare contour lines and detect invariant peaks for CPs based on contour line shapes, which can generate good initial values of transformation parameters. Finally, the least squares surface matching technique is used for optimal matching. The proposed methodology is tested for DEM matching between a new InSAR DEM and ASTER DEM. The experimental results show that the proposed method shows considerable noise resistance and can alleviate deformation and nonlinear distortion effects of different systems.