Corradetti, Amerigo and McCaffrey, Ken and De Paola, Nicola and Tavani, Stefano (2017) 'Evaluating roughness scaling properties of natural active fault surfaces by means of multi-view photogrammetry.', Tectonophysics., 717 . pp. 599-606.
Fault roughness is a measure of the dimensions and distribution of fault asperities, which can act as stress concentrators affecting fault frictional behaviour and the dynamics of rupture propagation. Studies aimed at describing fault roughness require the acquisition of extremely detailed and accurate datasets of fault surface topography. Fault surface data have been acquired by methods such as LiDAR, laser profilometers and white light interferometers, each covering different length scales and with only LiDAR available in the field. Here we explore the potential use of multi-view photogrammetric methods in fault roughness studies, which are presently underexplored and offer the advantage of detailed data acquisition directly in the field. We applied the photogrammetric method to reproduce fault topography, by using seven dm-sized fault rock samples photographed in the lab, three fault surfaces photographed in the field, and one control object used to estimate the model error. We studied these topographies estimating their roughness scaling coefficients through a Fourier power spectrum method. Our results show scaling coefficients of 0.84 ± 0.17 along the slip direction and 0.91 ± 0.17 perpendicularly to it, and are thus comparable to those results obtained by previous authors. This provides encouragement for the use of photogrammetric methods for future studies, particularly those involving field-based acquisition, where other techniques have limitations.
|Full text:||(AM) Accepted Manuscript|
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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|Publisher Web site:||https://doi.org/10.1016/j.tecto.2017.08.023|
|Publisher statement:||© 2017 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Date accepted:||19 August 2017|
|Date deposited:||01 September 2017|
|Date of first online publication:||19 August 2017|
|Date first made open access:||19 August 2018|
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