• DocumentCode
    70458
  • Title

    Estimating Bedding Orientation From High-Resolution Digital Elevation Models

  • Author

    Cracknell, Matthew J. ; Roach, Michael ; Green, Dale ; Lucieer, Arko

  • Author_Institution
    ARC Centre of Excellence in Ore Deposits (CODES), Faculty of Science, Engineering and Technology, University of Tasmania, Hobart, Australia
  • Volume
    51
  • Issue
    5
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    2949
  • Lastpage
    2959
  • Abstract
    A high-resolution digital elevation model (DEM), generated from airborne light detection and ranging (LiDAR) remote sensing data, is used here to estimate the 3-D orientation of bedding planes. Methods for enhancement, manual identification and extraction of lineaments, and estimation of best fit planes representing bedding are presented and evaluated for a study area in folded metasedimentary rocks in northeast Tasmania, Australia. Estimated bedding plane dip directions are shown to be accurate and reliable when compared with field-based observations. The same cannot be said for dip angle estimates. It is likely that small errors in the location of a manually digitized lineament will affect dip estimation more than dip direction estimation, particularly for steeply dipping structures. Fold axis orientations calculated from the stereographic analysis of estimated bedding closely correspond to orientations determined from field data. The mean absolute differences \\pm standard error for 12 of the 14 regularly spaced domains located within the study area were 8.7^{\\circ} \\pm 1.2^{\\circ} for the fold plunge and 4.9^{\\circ} \\pm 0.9^{\\circ} for the fold trend. The techniques described here for the extraction of bedding plane orientations from high-resolution DEMs complement field-based geological mapping and can assist structural interpretations.
  • Keywords
    Australia; Digital elevation models; Geographic information systems; Geology; Laser radar; Surface morphology; Surface topography; Digital elevation model (DEM); Tasmania; geographic information system (GIS); geology; light detection and ranging (LiDAR); lineament; remote sensing;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2012.2217502
  • Filename
    6355651