Topography has a major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Land surface spatial structure that captures spatial heterogeneity influenced by topography is expected to improve representation of land surface processes in land surface models. For example, land surface modeling using subbasins instead of regular grids as computational units has demonstrated improved scalability of simulated runoff and streamflow processes. In our recent study exploring new land surface spatial structures based on topographic properties, we evaluated two (Global and Local) methods of watershed discretization using two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the Northwestern United States. Results showed that the Local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic, and vegetation variability important for land surface modeling. The Local method combines concepts of hypsometric analysis with landscape orientation to discretize each watershed into subgrid structures. To evaluate the role of landscape orientation in the Local method, non-geo-located subgrid structures are derived with and without landscape orientation over the Columbia River basin. Remote sensing data are then utilized to evaluate how landscape orientation improves capability of the Local method to capture vegetation and snow variability.