Road Extraction in Rural and Urban Areas

An approach for automatic road extraction from digital aerial imagery is presented. The extraction is based on a semantic model for roads. The images are divided into different so-called “global contexts”: rural, forest, and urban. Different parts of the road model and different strategies are used in the different global contexts. In rural areas, a multi-scale approach is employed to find initial hypotheses for roadsides, which are then grouped into road segments using local context knowledge. In urban areas, road markings and DEM information are used to extract road segments. In addition to the local grouping, road segments are selected and linked into a global road network. An external evaluation shows the high quality of the results that are obtainable automatically with the proposed approach.