A Framework for Road Change Detection and Map Updating

The updating of road network databases is crucial to many Geographic Information System (GIS) applications such as navigation, urban planning, etc. This paper presents a comprehensive framework for image-based road network updating, in which the following three tasks are performed sequentially: road extraction from imagery, road change detection and updating, and spatio-temporal modeling. For road extraction a multi-resolution analysis approach is used in combination with a novel road junction detection method. The road change detection and updating is one of the typical issues in the map conflation field. Feature matching techniques are applied to determine the changed and unchanged portions of the road network. A conflation step is then used to create an updated road network in which the attributes will be transferred from the existing database to the new database based on the conjugate features resulting from the feature matching step. For a pragmatic road updating system, a spatio-temporal modeler should be encompassed to efficiently and effectively store and make use of both the updated and old databases. The proposed methodology has been tested on updating the Canadian National Topographic DataBase (NTDB) based on road extraction from remotely-sensed imagery. * Corresponding author. Qiaoping Zhang – [email protected]