Topography exerts a major control on land surface processes through its influence on atmospheric forcing, properties of soil and vegetation, network topology (connectivity) 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 this study, a global subbasin dataset and other various surface datasets are developed from a more consistent high resolution global Digital Elevation Model developed in this effort. A local classification method is applied to derive a new land surface spatial structures defined by further dividing subbasins/grids into subgrid units topographic information to take advantage of the emergent patterns and scaling properties of atmospheric, hydrologic, and vegetation processes in land surface models. This presentation reports recent results.