Space-efficient terrain rendering using constrained Delaunay triangulation

Proposes a new terrain visualization technique associated with the conversion process from a contour-based data model to a triangulated irregular network (TIN) model. The main research related to processing these contour lines had been focused on interpolation methods to create the digital terrain model (DTM). We introduce a novel approach for visualizing terrain by using contour line data which are obtained from the digital elevation model (DEM). Our approach uses the marching square algorithm to extract contour lines from the DEM and classify contours into open contours and closed contours to calculate local minimum/maximum points. To minimize the search space for calculating local minimum/maximum, we construct the containment tree of the closed contour. Then we only achieve an approximation procedure for calculating minimum/maximum points at leaf nodes in the containment tree. Finally, we can easily reconstruct the terrain by performing constrained Delaunay triangulation that uses approximation points and contour data as inputs. In the experiments, we compare our algorithm with DEM processing in terms of the processing speed and data size.