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
standard error for 12 of the 14 regularly spaced domains located within the study area were
for the fold plunge and
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
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