Digital Elevation Models (DEM) have become important tools in many remote sensing applications, such as classification, defense, Geographic Information Systems, etc. But they are complex products to generate and they are still pervaded with errors and artifacts due to the generation techniques themselves or atmospheric problems. Thus their qualification for a specified application is not guaranteed. It is well known nowadays that the evaluation of the quality of a DEM is a challenging task, due to the variety of requirements depending on the applications and on the end-user. It remains a major field of investigation, where scientists always look for new tools for the analysis of DEM. The use of multiresolution techniques is one possible answer to this research. In the past decades it has been shown that natural landscapes exhibit fractal behaviors. Consequently it seems rather obvious and relevant to use techniques based on fractals and more generally on multi resolution concepts as a tool for understanding the geological nature of terrain. Thanks to the emergence of the use of the wavelet theory, researchers get interested again in fractals modeling for geo information processing and understanding. In this article our aim is to present the various analysis that are possible to lead on DEM thanks to multi resolution methods, in particular wavelet filtering and fractal dimension estimation.