Graph-supported verification of road databases

The verification of existing data is an important task in order to ensure a high level of data quality, such as is needed in geographic information systems (GIS). Today, this work is carried out manually by an operator, who compares vector data from databases with remotely sensed imagery. In this paper, a system for automated road data verification using digital image processing for the extraction of roads from aerial imagery and topological analysis in order to optimise the whole process in terms of reliability and efficiency is presented. The main goal is to call the operator's attention only to parts of the network, where the automated process did not find sufficient evidence of a road. The road extraction is supported by the use of prior knowledge on the global level (whether the road is situated in rural, urban or forest areas), and information on the road geometry and its attributes. The road extraction is executed twice. Firstly, with a strict parameter control ensuring the minimization of false positives and a subsequent evaluation, which denotes roads from the database being accepted or rejected. In a second step, a graph-based search algorithm detects connections, which are missing for an optimised road network. If rejected roads are part of these connections, they are checked again using a more tolerant parameter control. A detailed performance analysis of results shows the applicability of the proposed method for quality control of topographic road databases.