Multiscale Integrating Algorithm on the Road Features Extracted from IKONOS Satellite Imagery and Topographic Map

摘要

Integration and updating of multi scale geospatial data is a key technology in Geomatics. Road networks are multi scale spatial datasets that need more details and high accuracy in main area of city and low details and accuracy in the area of outside city. The changes of road networks extracted from IKONOS imagery are a more efficiency and low costs method in local area. Aiming to automate road networks mapping, a approach for semi-automatic extraction of road networks from IKONOS imagery is given by author. In the first step of the proposed approach, the centerline of road is extracted from GIS spatial database. The road changes can be outlined in IKONOS imagery contrasting with road vector data. Then, we update the road changes. Road centerline can be extended to road boundary by the road widths acquiring from imagery measure. Test results show that the proposed approach is capable of extracting road networks from IKONOS images and also saving human work time. Map conflation is used to integrate the spatial data of multi scale and multi resource into unifying spatial datasets. Conflation describes procedures that merge data from different sources into a new, best dataset that is a combination of the original datasets. The cyber-city project using above methods has been finished and the quality is good.