InSAR and Optical Constraints on Fault Slip during the 2010-2011 New Zealand Earthquake Sequence

Evolution of the 2010–2012 Canterbury earthquake sequence

“…1) (Ristau 2008;Sibson et al 2011), consistent with slip on either a northÁnorthwestÁ southÁsoutheast-striking or eastÁnortheastÁwestÁsouth-west-striking fault plane. Results from separate geodetic and strong motion inversions indicate that two distinct patches of slip occurred either on intersecting fault planes or on a single fault oriented northÁnorthwestÁsouthÁsoutheast; the former interpretation is preferred by Beavan et al (2012), while a single fault plane with an eastÁnortheastÁwestÁsouthwest orientation was preferred by Barnhart et al (2011). The 13 June earthquakes were immediately followed by aftershock activity extending towards Port Levy and Pigeon Bay, along a distinct northÁnorthwestÁsouthÁsoutheast trend (Fig.…”

Evidence for slip partitioning and bimodal slip behavior on a single fault: Surface slip characteristics of the 2013 Mw7.7 Balochistan, Pakistan earthquake

“…1,2). SPC techniques are commonly applied to constrain co-seismic rupture displacements (e.g., Michel et al, 1999;Dominguez et al, 2003;Avouac et al, 2006;Leprince et al, 2008;Oskin et al, 2012), glacial surface velocities (e.g., Scambos et al, 1992;Kääb, 2002;Berthier et al, 2005;Stearns et al, 2005;Debella-Gilo and Kääb, 2011;Willis et al, 2012;Melkonian et al, 2013), and landslide motions (e.g., Kääb, 2002;Delacourt et al, 2004). Use of high-resolution commercial images in such studies are advantageous for several reasons: increased spatial resolution over imagery such as Landsat-8, increased temporal resolution because of the ability to direct satellite viewing geometries, and the ability to analyze imagery from multiple sensors (e.g., Barnhart et al, 2011).…”

Geodetic Constraints on the 2014 M 6.0 South Napa Earthquake

“…S2). We implement a Monte Carlo error propagation approach (Barnhart et al, 2011) wherein we generate 1000 synthetic noisy data sets by adding Gaussian distributed random noise to the predicted displacements from our best SDs. All observations and corresponding Green's functions are preweighted by the Cholesky inverse of the noise covariance matrix ; thus, the spatially correlated nature of the InSAR noise and the nonspatially correlated nature of the GPS noise are both accounted for when Gaussian noise is added.…”