A novel computational paradigm for creating a Triangular Irregular Network (TIN) from LiDAR data Original Research Article

The Triangular Irregular Network (TIN) model is an alternative to the grid-based representation of the terrain surface adopted in numerous digital mapping and geographic information systems. In TIN, irregularly spaced sample points model the terrain in such a way that more points represent the areas with rough terrain and there are fewer in smooth terrain. Despite its simplicity, creating a TIN model for an area involves (a) picking sample points, (b) connecting points into triangles, and (c) modeling the surface within each triangle. Most of the available algorithms for picking sample points use either a dense Digital Elevation Model (DEM) or a set of digitized contours as input. Now, the availability and popularity of Light Detection And Ranging (LiDAR) devices, which produce clouds of points, require the development of a new computational paradigm for picking sample points from the new data. This article presents a novel computational framework for picking sample points to create a TIN model from LiDAR data.