Refinement of Digital Elevation Models in Urban Areas Using Breaklines Via a Multi-Photo Least Squares Matching Algorithm

High quality DEMs are necessary for several urban applications such as telecommunication, urban development, and visualization, and city planning and management. Sudden changes in surface topography weaken the capability of existing automatic terrain extraction techniques to provide high quality DEMs. Hence, these DEMs need to be refined either manually or automatically to be useful for such applications. Manual refinement is costly and time consuming, thus automatic refinement is preferred. In this research, three new DEM refinement approaches are demonstrated. In the first approach only breaklines are utilized, while the second approach incorporates image signals in a least squares matching model. In the third approach, pixels corresponding to hidden objects are detected and eliminated from the least squares matching model. Breaklines are used in the three approaches to impose surface discontinuity. The least squares matching model minimizes the differences between the image intensities by adjusting the elevations of the DEM posts. The refining approaches are tested on eight one-meter resolution DEMs. The DEMs are generated with a digital-mapping software from 1:4000 scale aerial photographs scanned at 30μm resolution. Results revealed that the accuracy of the DEMs is considerably improved using the third approach and demonstrate its benefit in refining DEMs especially for urban area applications.