A DEM generalization by minor valley branch detection and grid filling

As an important method of terrain representation, a DEM usually needs to be generalized at multiple resolutions in order to adapt to different applications. The preservation of main landscape features is an important constraint in DEM generalization. The traditional generalization method based on signal processing by resampling or low-pass filtering is just a data compression operation rather than the abstraction of real information. This study develops a structured analysis method to generalize DEM data through the identification of minor valleys and filling the corresponding depression positions. The generalization process has two steps: geographic decision and geometric operation. According to their hydrological significance, the unimportant valley branches are detected and their corresponding coverage is filled by raising the terrain to make the terrain surface smoother. In contrast to the conventional algorithms based on image processing, this method is able to retain the main geographical characteristics more effectively in terrain representation.