The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 935–941, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-935-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 935–941, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-935-2019

  05 Jun 2019

05 Jun 2019

POTENTIAL AND LIMITATIONS OF TERRESTRIAL LASER SCANNING FOR DISCONTINUITY ROUGHNESS ESTIMATION

M. Bitenc1, D. S. Kieffer1, and K. Khoshelham2 M. Bitenc et al.
  • 1Institute of Applied Geosciences, Graz University of Technology, Austria
  • 2Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010, Australia

Keywords: Terrestrial Laser Scanning, Range noise, Effective resolution, Discontinuity roughness, Stationary Wavelet Transform

Abstract. Terrestrial Laser Scanning (TLS) greatly facilitates the acquisition of detailed and accurate 3D measurements of remote rock outcrops, at an operational range from several meters to a few kilometres. Reliable, quantitative measures of rock discontinuity roughness are necessary to characterize and evaluate the mechanical and hydraulic behavior of the rock mass. The aim of this research is to investigate the TLS potential and limitations for a reliable estimation of small scale roughness. TLS data noise and resolution define the level of extractable morphological detail, and therefore need to be known and associated with roughness value. The stationary variant of Discrete Wavelet Transform (SWT) was applied to estimate TLS noise level and perform wavelet denoising in direction of range measurements. Denoised TLS data were compared to reference surfaces of decreasing resolution (reference grids) in order to define the size of extractable surface detail. Noise and resolution effect on rock surface roughness, wavelet denoising success and extractable roughness scale were investigated with comparative analyses of TLS and reference surfaces. The developed methodology enabled reasonable TLS noise estimation, improved capabilities of TLS for modelling fine features of an irregular rock surface, and indicated the surface scale that can be reliably extracted from the TLS data.