DEM generation from lidar data in wooded mountain areas by cross-section-plane analysis

Ground filtering for airborne lidar data is a challenging task for the generation of digital terrain models (DTMs) in wooded mountain areas. To solve this problem, this article, based on cross-section-plane (CSP) analysis, presents a CSP-based stepwise filtering strategy that can automatically separate terrain from non-terrain points. The filtering strategy consists of four main computing steps: (a) ‘split’ – the raw lidar data are partitioned into 3D cells, in each of which multi-directional CSPs are generated at multiple directions; (b) ‘filter’ – the potential terrain points are selected for each CSP according to lidar data characteristics, such as multi-returns, intensity, and height; (c) ‘detect’ – the initial terrain points are detected for each CSP by exploring distances and slopes between nearby points; and (d) ‘adjust-and-refine’ – the terrain points are extracted from all initial terrain points of all CSPs by a merging-or-intersecting strategy and a five-point refinement. The extensive experiments using three lidar data sets demonstrated that the CSP-based stepwise filtering method is capable of producing reliable DTMs in densely forested mountain areas.