ABSTRACT
We present a method to extract elevated road structures, typically overpassing other roads, transit lines, and watercourses. The technique uses a digital surface model (DSM) and roughly aligned vector road data and outputs geometry approximating the shape and elevation of the elevated road deck. Our method is robust against noise in DSM elevations and can recover elevated roads partially obscured by trees and other overpasses. We demonstrate our method parallelized over city-wide DSMs, and formulate a confidence metric ranking the fidelity of the reconstruction.
- N. Akel, K. Kremeike, S. Filin, M. Sester, and Y. Doytsher. Dense DTM generalization aided by roads extracted from LiDAR data. pages 54--59, 2005.Google Scholar
- J. Dean and S. Ghemawat. Mapreduce: simplified data processing on large clusters. Commun. ACM, 51:107--113, January 2008. Google ScholarDigital Library
- W. A. Harvey and J. McKeown, David M. Automatic compilation of 3D road features using LIDAR and multi-spectral source data. In ASPRS 2008 Annual Conference, Portland, Oregon, April 28 - May 2 2008.Google Scholar
- M. T. Jong-Hyeok Jeong. Extraction of bridge positons from IKONOS images for accuracy control of bridge database.Google Scholar
- N. Loménie, J. Barbeau, and R. Trias-Sanz. Integrating textural and geometric information for an automatic bridge detection system. In Proc. of the 2003 International Geosciences And Remote Sensing Symposium (IGARSS 2003), Toulouse, France, July 2003.Google ScholarCross Ref
- S. J. Oude Elberink. Acquisition of 3D topography: automated 3D road and building reconstruction using airborne laser scanner data and topographic maps. PhD thesis, University of Twente, Enschede, April 2010.Google Scholar
- C. Qian, B. Gale, and J. Bach. Earth documentation: Overpass detection using mobile LiDAR. In Image Processing (ICIP), 2010 17th IEEE International Conference on, pages 3901--3904, September 2010.Google ScholarCross Ref
- G. Sithole and G. Vosselman. Experimental comparison of filter algorithms for bare-earth extraction from airborne laser scanning point clouds. ISPRS Journal of Photogrammetry and Remote Sensing, 59(1--2):85--101, 2004.Google ScholarCross Ref
- R. Trias-Sanz and N. Loménie. Automatic bridge detection in high-resolution satellite images. In Proceedings of the 3rd international conference on Computer vision systems, ICVS'03, pages 172--181, Berlin, Heidelberg, 2003. Springer-Verlag. Google ScholarDigital Library
- C. Valla. Postcards from Google Earth, bridges, 2010. http://clementvalla.com/index.php?/work/bridges/.Google Scholar
Index Terms
- Geometric overpass extraction from vector road data and DSMs
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