Constraining recent fault offsets with statistical and geometrical methods: Example from the Jasneuf Fault (Western Alps, France)

Billant, Jérémy; Bellier, Olivier; Godard, Vincent; Hippolyte, Jean-Claude

doi:10.1016/j.tecto.2016.09.031

Cited by 5 publications

(6 citation statements)

References 52 publications

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“…Close‐range SfM photogrammetry has become an extremely powerful tool to acquire georeferenced topographic models from simple and lightweight devices, also allowing to produce spectral orthophotographies. SfM photogrammetry appears as an efficient tool for reconstructing earthquake offsets and tectonic structural analysis and determining surface displacement fields (e.g., Bemis et al, ; Billant et al, ; Escartin et al, ; Johnson et al, ; Lucieer et al, , Shervais & Kirkpatrick ). The principle of SfM photogrammetry has been reviewed largely in the literature (James & Robson, ; Westoby et al, ).…”

Section: Results From Photogrammetry Datamentioning

confidence: 99%

Coseismic Slip Vectors of 24 August and 30 October 2016 Earthquakes in Central Italy: Oblique Slip and Regional Kinematic Implications

et al. 2018

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After 24 August and 30 October 2016 central Italy earthquakes (Mw 6.0 and 6.5, respectively), photogrammetry and geodetic survey were performed at various sites along a 6-km-long portion of the rupturing Monte Vettore fault system, providing very high-resolution georeferenced 3-D point clouds and imagery of the 24 August rupture and a data set of bedrock fault scarp before/after the 30 October earthquake. The maximum coseismic displacement for both events occurs near Scoglio dell' Aquila with an average normal dip slip of 22 ± 4 and 184 ± 6 cm, respectively. Coseismic slip vectors and meter-scale corrugation axis are oriented N280 ± 10°on the~N140°striking main Vettore fault involving oblique normal slip with a right-lateral component and N205 ± 10°on~N170°fault strands implying oblique normal slip with a left-lateral component. We quantify the near-field coseismic displacements of the Monte Vettore fault for the 30 October event: the footwall has been translated horizontally by 42 ± 2 cm toward the ENE and uplifted by 11 ± 2 cm. The hangingwall has moved horizontally by 26 ± 2 cm, toward the NW, in a direction parallel to the fault plane and subsided by 116 ± 2 cm. The fault geometry and our determined surface coseismic slip vectors are mechanically compatible with a σ3 = N65 ± 15°. This stress regime is consistent with the 30 October 2016 focal mechanism and the relative motion between the Adriatic microplate and the Tyrrhenian coastal region. The 30 October surface rupture results from seismic slip at depth and thus has a tectonic origin. Plain Language SummaryAfter 24 August and 30 October 2016 central Italy earthquakes, we acquire a very high-resolution data set of the effect of the fault at the surface before and after the 30 October earthquake. Those data sets allow quantifying the motion of each compartment on both side of the fault during the earthquake and the direction of this motion. The footwall has been translated horizontally by 42 ± 2 cm toward the ENE and uplifted by 11 ± 2 cm. The hangingwall has moved horizontally by 26 ± 2 cm, toward the NW, and subsided by 116 ± 2 cm. These results are consistent with the seismic data and suggest that surface ruptures observed are resulting from seismic slip at depth.In 2016, Italy was struck by an earthquake sequence that lasted several months with three shocks on 24 August, Mw = 6.0; 26 October, Mw = 5.9; and 30 October, Mw = 6.5 (Figure 1). This sequence occurred in Central Apennines, where NW-SE striking normal fault systems are accommodating~4 mm/year of PEROUSE ET AL. 3760

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Section: Results From Photogrammetry Datamentioning

confidence: 99%

Coseismic Slip Vectors of 24 August and 30 October 2016 Earthquakes in Central Italy: Oblique Slip and Regional Kinematic Implications

et al. 2018

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“…In addition to lateral offsets, 3D_Fault_Offsets provides a systematic and rich compilation of the vertical offsets. This opens new opportunities to examine the different slip components and their ratios on the faults (see also Billant et al, ; Mackenzie & Elliott, ), as the relations between alluvial dynamics and fault motion (e.g., Ouchi, ). 3D_Fault_Offsets also provides a means to quantify the trimming of the channel banks that results from the combination of alluvial dynamics and lateral fault slip.…”

Section: Discussionmentioning

confidence: 99%

“…More recently, the explosion of high‐resolution topographic data, especially Lidar that allows the measurement of the bare Earth surface at ≤1 m resolution (e.g., Arrowsmith & Zielke, ; Bevis et al, ; De Pascale et al, ; Frankel et al, ; Haddad et al, ; Lin et al, ; Meigs, ; Zielke et al, ; Zielke et al, ), has motivated the development of new, automatized approaches to remotely measure fault slips in the topographic data. These approaches, so far, use an overall measure of the topography (Billant et al, ), planar surfaces (Mackenzie & Elliott, ), or linear geomorphic features (Haddon et al, ; Zielke et al, ; Zielke & Arrowsmith, ) as recorders and markers of the fault displacements. In particular, Zielke and Arrowsmith () and Zielke et al () have developed a Matlab code, LaDiCaoz (updated version, LaDiCaoz_v2, released by Haddon et al, ), to semiautomatically measure fault offsets across ubiquitous linear geomorphic features such as stream channels and terrace risers.…”

Section: Introductionmentioning

confidence: 99%

“3D_Fault_Offsets,” a Matlab Code to Automatically Measure Lateral and Vertical Fault Offsets in Topographic Data: Application to San Andreas, Owens Valley, and Hope Faults

et al. 2018

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Measuring fault offsets preserved at the ground surface is of primary importance to recover earthquake and long‐term slip distributions and understand fault mechanics. The recent explosion of high‐resolution topographic data, such as Lidar and photogrammetric digital elevation models, offers an unprecedented opportunity to measure dense collections of fault offsets. We have developed a new Matlab code, 3D_Fault_Offsets, to automate these measurements. In topographic data, 3D_Fault_Offsets mathematically identifies and represents nine of the most prominent geometric characteristics of common sublinear markers along faults (especially strike slip) in 3‐D, such as the streambed (minimum elevation), top, free face and base of channel banks or scarps (minimum Laplacian, maximum gradient, and maximum Laplacian), and ridges (maximum elevation). By calculating best fit lines through the nine point clouds on either side of the fault, the code computes the lateral and vertical offsets between the piercing points of these lines onto the fault plane, providing nine lateral and nine vertical offset measures per marker. Through a Monte Carlo approach, the code calculates the total uncertainty on each offset. It then provides tools to statistically analyze the dense collection of measures and to reconstruct the prefaulted marker geometry in the horizontal and vertical planes. We applied 3D_Fault_Offsets to remeasure previously published offsets across 88 markers on the San Andreas, Owens Valley, and Hope faults. We obtained 5,454 lateral and vertical offset measures. These automatic measures compare well to prior ones, field and remote, while their rich record provides new insights on the preservation of fault displacements in the morphology.

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“…Elliott et al (2012b) combined pairs of nearby planform markers across the Darfield fault to calculate the magnitude and orientation of the horizontal component of the slip vector, assuming that both markers were subjected to the same slip vector. Billant et al (2016) amassed suites of apparent topographic offsets to define both the horizontal and vertical components of a single slip vector represented by adjacent contour separations. We extend these concepts to exploit the change in apparent landform offset with varying marker geometry.…”

Section: Slip Geometry: 3d Analysismentioning

confidence: 99%

“…4, p. , doi:10.1130 the information provided by the full topography field. The resulting slip distributions are almost always variable and noisy and it is often unclear whether this reflects real slip variation or artifacts of measurement noise, erosion, and slip geometry (e.g., Haeussler et al, 2004;Klinger et al, 2006;Elliott et al, 2012b;Schwartz et al, 2012;Rockwell and Klinger, 2013;Billant et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Untangling tectonic slip from the potentially misleading effects of landform geometry

Mackenzie

Elliott

2017

Geosphere

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We present a new three-dimensional (3D) approach to the analysis of fault scarps using high-resolution elevation models. Advances in topographic measurement techniques [e.g., lidar (light detection and ranging) and photogrammetric techniques] have allowed extensive measurement of single earthquake and cumulative scarps to draw conclusions about along-strike slip variation and fault slip history. The resulting slip distributions are almost always variable and noisy, but the cause is often unclear. We first present the results of sensitivity analysis to demonstrate significant apparent noise due to varying terrain and fault and measurement geometry (topographic slope attitude, fault dip and slip obliquity). We show, with a case study on the Hoshab fault, Pakistan, that oblique slip can have a significant effect on the measured apparent slip. Individual planar geomorphic markers only constrain one component of the full 3D slip vector. We use the variation in apparent offset with marker geometry to constrain the slip vector in 3D. Combining multiple offset measurements along strike, we show that determining the slip vector is reduced to a simple linear formulation. We test our method using a terrestrial lidar data set from the ruptures on the Borrego fault from the 2010 El Mayor-Cucapah earthquake (Baja California, Mexico). Combining 22 observations, we estimate a throw of 1.56 ± 0.02 m and a lateral slip of 1.9 ± 0.3 m. The vertical slip estimate agrees well with previous studies, but the lateral slip is significantly smaller. In regions of steep varied topography or with oblique slip, our method will give enhanced slip resolution while standard methods will give biased estimates.

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Constraining recent fault offsets with statistical and geometrical methods: Example from the Jasneuf Fault (Western Alps, France)

Cited by 5 publications

References 52 publications

Coseismic Slip Vectors of 24 August and 30 October 2016 Earthquakes in Central Italy: Oblique Slip and Regional Kinematic Implications

Coseismic Slip Vectors of 24 August and 30 October 2016 Earthquakes in Central Italy: Oblique Slip and Regional Kinematic Implications

“3D_Fault_Offsets,” a Matlab Code to Automatically Measure Lateral and Vertical Fault Offsets in Topographic Data: Application to San Andreas, Owens Valley, and Hope Faults

Untangling tectonic slip from the potentially misleading effects of landform geometry

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