ORCID Profile
0000-0002-1869-1044
Current Organisation
Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-12595
Abstract: Mapping and characterisation of crustal faults represent one of the contemporary challenges for both tectonic understanding and seismic hazard assessment. Given the high resolution of satellite-derived digital elevation models and remote-sensing imagery, the development of an automatic method of fault extraction is a critical turning point. Here we present a Python-based, open-source workflow,& which is able to extract and characterize in idual faults as well as entire fault networks from various datasets.& Our workflow consists of four main steps: (1) The DEM contains different types of noise, which we reduce using Gaussian smoothing. (2) Then we use the Canny edge detection to highlight topographic discontinuities, such as faults. (3) These edges are simplified in single pixel-wide lines through the skeletonization algorithm. (4) Finally, we create a network consisting of nodes and edges from this skeleton. After a few post-processing steps we obtain a fault network of the s le area.& We use the toolbox to study faulting in the East African Rift system, especially the Magadi Natron basin. The workflow was applied to a TanDEM-X digital elevation model with 12 m horizontal resolution and the Copernicus GLO-30 dataset with 30 m average horizontal resolution. The strike analysis shows four main directions from distinct fault populations. Moreover, we derive the fault displacement distribution throughout the basin, which allows us to calculate the total orthogonal extension of each geological unit and to compute the overall amount of extension of the region during geologically recent times.Our workflow is designed to evaluate topographic data of target sites in nature, it can, however, also be used to analyze analogue models and numerical simulations. To this aim, specific functions can be added in a modular way to suit the particularity of the area and of available data types. This workflow allows us to imagine a very wide range of applications and subjects of interest.
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-10695
Abstract: & & Continental rifts show surface expressions of deep crustal processes, such as faulting and volcanism. The East African Rift System (EARS) is one of the most prominent ex les of an active continental rift driven by tectonics and magmatism. Nonetheless, we still struggle to quantify the amount of extension due to these processes on a kyr- to Myr-time-scale. In particular, the distribution of extension within low-offset normal fault networks within rift basin interiors is challenging to determine.& & & & To address these issues, we develop a semi-automated workflow to extract normal faults from the TanDEM-X science DEM data (12 m horizontal resolution, 0.4 m average height error) of the Magadi-Natron Region of the Eastern branch of the EARS, limited to the north by the Suswa caldera (1.15& #176 S) and to the south by Gelai and Oldoinyo Lengai volcanoes (2.75& #176 S). This data allows us to quantify brittle surface deformation that occurred since the last deposition of widespread volcanic lavas in& these basins. Our workflow consists of five steps: (1) gradient calculation, (2) thresholding, (3) skeletonization, (4) Hough transformation, and (5) clustering. Because the surface faults appear as topographic discontinuities, we first calculate the gradient of the DEM to detect them. Then we use an adaptive threshold (Otsu) to distinguish faults from unfaulted areas. Next, we skeletonize the threshold to extract line segments and perform a Hough transformation to determine the orientation of these segments. Finally, we use a density-based clustering algorithm (DBSCAN) to group these segments into faults. This algorithm is considering proximity between the segment, similarity in dip and strike direction.& & & & A strike analysis applied on the fault data of the whole basin shows four main directions from distinct fault populations. Each direction cluster corresponds to a geological layer and a time interval. For ex le, the azimuth N20& #176 , corresponds to present and recent rift direction, mostly on the ~1Myr old Magadi trachyte. A direction of N170& #176 is mostly represented in earlier,& Mio-Pliocene volcanic units of the rift. Moreover, we derive the fault displacement distribution throughout the basin.This allows us to calculate the total extension of each geological unit and to compute the overall amount of extension of the region during geologically recent times.& & & & We provide a new high-resolution fault map that depicts strike direction and throw even of small-offset normal faults. This characterization helps us increase our understanding of recent brittle deformation within the Magadi-Natron region and thus the propagation of rifting in the eastern branch of the East African Rift System.& &
Location: Germany
No related grants have been discovered for Pauline Gayrin.