Robust DEM co-registration method for terrain changes assessment using least trimmed squares estimator Original Research Article

Robust DEM co-registration for detecting terrain changes is an attractive but unresolved problem in both Remote Sensing and the Prevention and Mitigation of Hazards. Since robust DEM co-registration is an inherently very difficult problem, the algorithms developed are becoming more and more complicated. In this paper, a robust method for DEM co-registration is proposed, which integrates the least trimmed squares (LTS) estimator with the least Z-difference (LZD) algorithm. Moreover, a self-adaptive threshold based on the histogram of height differences is employed to identify the terrain changes automatically, which are the fundamental data for landslide assessment. The results of simulated experiments illustrate the robustness and accuracy of the new algorithm.