Abstract: In this paper, taking DEM data as an example, the input data and the reference data are firstly aligned to the same pixel position, then the root mean square error and standard deviation are taken as reference indicators, and the best weighting fusion coefficients are explored by the traversal process of weighting coefficients from 0 to 1 in the regions of different slope classes. To determine the fusion scheme and perform the fusion of NASA DEM and AW3D30 DEM, and finally evaluate the fusion effect quantitatively. The results show that before the alignment, the displacements of NASA DEM along x, y, and z directions are -2.65, 2.41, and 0.60m, and the displacements of AW3D30 DEM are 1.04, 7.51, and -3.33m; after the alignment, all the errors of the original data are reduced, and the systematic errors of NASA DEM disappear. Compared with the NASA DEM, the ME and RMSE of the fused DEM are reduced by 25.0% and 36.8%; for the AW3D30 DEM, the error reduction is 86.5%, and 13.2%.

Key words: NASA DEM, AW3D30 DEM, least squares alignment, weighted fusion, Taiyuan