SHADED-RELIEFS MATCHING AS AN EFFICIENT TECHNIQUE FOR 3D GEO- REFERENCING OF HISTORICAL DIGITAL ELEVATION MODELS

Traditional methods using aerial photographs for shoreline measurement often involved non-stereo photography with no vertical information. However, digital elevation models (coastal elevation models or CEMs in our case) are widely used in GIS to predict the impact of coastal flooding and Sea Level Rise. Hence, we propose the CEM methodology to cope with computing shoreline position as the interface between the land and the water at a previously chosen vertical datum. Furthermore, CEM evolution during the studied period may be used to quantify the coastal landscape changes. In any case an accurate CEM is needed, both for newly-made CEMs and for historical CEMs mostly compiled from historical photogrammetric flights. A new approach to historical CEM 3D geo-referencing is proposed along this work to avoid the costly and time-consuming necessity of ground control points. The proposed methodology was tested for geo-referencing a historical grid format CEM, comprising a little coastal area of Almeria (South Spain), obtained by digital stereo-photogrammetry from a B&W photogrammetric flight taken in 1977 at an approximated scale of 1:18000. The reference CEM was the 10 m grid-spacing digital elevation model produced by the Andalusia Regional Government (Spain) coming from a 1:20000 scale W&B photogrammetric flight made in 2001. The results obtained from this work may be deemed as very promising, showing a high efficiency for historical CEM 3D geo-referencing when it was compared to traditional methods such as photogrammetric absolute orientation based on surveyed ground control points and self-calibrating bundle adjustment techniques. This preliminary approach could be used as a previous course matching to be subsequently refined by 3D robust surface matching.

[1]  K. E. Anderson,et al.  Coastal Sensitivity to Sea-Level Rise: A Focus on the Mid-Atlantic Region , 2009 .

[2]  J. Brock,et al.  The Emerging Role of Lidar Remote Sensing in Coastal Research and Resource Management , 2009 .

[3]  Stuart Marsh,et al.  A robust surface matching technique for coastal geohazard assessment and management , 2008 .

[4]  Tim Webster,et al.  Flood-risk mapping for storm-surge events and sea-level rise using lidar for southeast New Brunswick , 2006 .

[5]  Thomas Integrating Uncertainty Theories with GIS for Modeling Coastal Hazards of Chimate Change , 2003 .

[6]  Manuel Ángel,et al.  Self-calibration methods for using historical aerial photographs with photogrammetric purposes , 2009 .

[7]  James C. Tison Marine geodesy , 1968 .

[8]  Manuel A. Aguilar,et al.  Modelling vertical error in LiDAR-derived digital elevation models , 2010 .

[9]  F. Algostino,et al.  International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIV-5/W10 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIV-5/W10 3D MODELING OF BOCCACCIO’S HOMETOWN THROUGHT A MULTISENSOR SURVEY , 2003 .

[10]  Manuel A. Aguilar,et al.  Developing digital cartography in rural planning applications , 2007 .

[11]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[12]  Tonggang Zhang,et al.  Robust DEM co-registration method for terrain changes assessment using least trimmed squares estimator , 2008 .

[13]  N. Barrand,et al.  Extracting photogrammetric ground control from lidar DEMs for change detection , 2006 .