Automatic Completion and Evaluation of Road Networks

Road networks automatically extracted from digital imagery are in general incomplete and fragmented. Completeness and topology of the extracted network can be improved by the use of the global network structure which is a result of the function of roads as part of the transport network. This is especially – but not exclusively – important for the extraction of roads from imagery with low resolution (e.g., ground pixel size > 1 m) because only little local evidence for roads can be extracted from those images. In this paper, an approach is described for the completion of incompletely extracted road networks. The completion is done by generating link hypotheses between points on the network which are likely to be connected based on the network characteristics. The proposed link hypotheses are verified based on the image data. A quantitative evaluation of the achieved improvements is given. New developments presented in this paper are the generation of link hypotheses between different connected components of the extracted road network and the introduction of measures for the evaluation of the network topology and connectivity. Results of the improved completion scheme are presented and evaluated based on the introduced measures. The results show the feasibility of the presented completion approach as well as its limitations. Major advantages of the completion of road networks are the improved network topology and connectivity of the extraction result. The new measures prove to be very useful for the evaluation of network topology and connectivity.