Optimization of Digital Elevation Models for Routing

Routing is a common task when using digital maps, but most engines offer only travel routes for automobiles. However, a more interesting aspect in this topic arises when being a cyclist. For this target audience especially elevation information is relevant. Such data is available from different sources, but is not perfectly usable for cycling routing. Those digital elevation models may include voids and outliers that falsify the elevation profile. Thus, a pre-processing step is necessary before using them. Therefore noise reduction steps and the Mean and Kalman filters are applied and evaluated in this work. They successfully eliminate erroneous and noisy information and smooth the elevation profiles. This enables a elevation aware routing engine to find and calculate more suitable paths for a cyclist, thereby allowing a more accurate route planning.