multi-resolution TIN model is an important issue in the contexts of visualization, virtual reality (VR), and geographic information systems (GIS). This paper proposes a new method for constructing multi-resolution TIN models with multiscale topographic features preservation. The proposed method is driven by a half-edge collapse operation in a greedy framework and employs a new quadric error metric to efficiently measure geometric errors. We define topographic features in a multi-scale manner using a center-surround operator on Gaussian-weighted mean curvatures. Experimental results demonstrate that the proposed method performs better than previous methods in terms of topographic features preservation, and is able to achieve multi-resolution TIN models with a higher accuracy.