2017
DOI: 10.1016/j.quaint.2016.09.034
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Locating distributed faulting: Contributions from InSAR imaging to Probabilistic Fault Displacement Hazard Analysis (PFDHA)

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Cited by 20 publications
(33 citation statements)
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“…Such a co-seismic deformation field, well imaged by remote sensing (i.e. InSAR data), is spatially correlated with DF also in areas far from the primary rupture (Livio et al, 2016), partially explaining an occurrence of DF more frequent than predicted from distance-based regressions. Earthquake-induced permanent strain can in fact result in the reactivation of pre-existing structures as compliant faults accommodating elastic deformation or in the promotion of new localized ground breaks.…”
Section: Shortcomings With the Database For Probabilistic Fault Displmentioning
confidence: 92%
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“…Such a co-seismic deformation field, well imaged by remote sensing (i.e. InSAR data), is spatially correlated with DF also in areas far from the primary rupture (Livio et al, 2016), partially explaining an occurrence of DF more frequent than predicted from distance-based regressions. Earthquake-induced permanent strain can in fact result in the reactivation of pre-existing structures as compliant faults accommodating elastic deformation or in the promotion of new localized ground breaks.…”
Section: Shortcomings With the Database For Probabilistic Fault Displmentioning
confidence: 92%
“…It is clear that the total area affected by co-seismic deformation can be considered a good proxy for earthquake magnitude. Although focal depth and faulting type remain important parameters, they do not significantly affect the overall log-linear relationship of the regressed variables (Livio et al, 2016). (Youngs et al, 2003), (b) strike-slip faults (Petersen et al, 2011), and (c) reverse and strike-slip faults in Japan (Takao et al, 2013).…”
Section: Shortcomings With the Database For Probabilistic Fault Displmentioning
confidence: 99%
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