@article{BarthGeertsemaBevingtonetal.2019,
  author    = {Barth, Sophia and Geertsema, Marten and Bevington, Alexandre R. and Bird, Alison L. and Clague, John J. and Millard, Tom and Bobrowsky, Peter T. and Hasler, Andreas and Liu, Hongjiang},
  title     = {Landslide response to the 27 October 2012 earthquake (M-W 7.8), southern Haida Gwaii, British Columbia, Canada},
  series = {Landslides : journal of the International Consortium on Landslides, ICL},
  volume    = {17},
  journal   = {Landslides : journal of the International Consortium on Landslides, ICL},
  number    = {3},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1612-510X},
  doi       = {10.1007/s10346-019-01292-7},
  pages     = {517 -- 526},
  year      = {2019},
  abstract  = {In this paper, we examine the influence of the 27 October 2012, M-w 7.8 earthquake on landslide occurrence in the southern half of Haida Gwaii (formerly Queen Charlotte Islands), British Columbia, Canada. Our 1350 km(2) study area is undisturbed, primarily forested terrain that has not experienced road building or timber harvesting. Our inventory of landslide polygons is based on optical airborne and spaceborne images acquired between 2007 and 2018, from which we extracted and mapped 446 individual landslides (an average of 33 landslides per 100 km(2)). The landslide rate in years without major earthquakes averages 19.4 per year, or 1.4/100 km(2)/year, and the annual average area covered by non-seismically triggered landslides is 35 ha/year. The number of landslides identified in imagery closely following the 2012 earthquake, and probably triggered by it, is 244 or an average of about 18 landslides per 100 km(2). These landslides cover a total area of 461 ha. In the following years-2013-2016 and 2016-2018-the number of landslides fell, respectively, to 26 and 13.5 landslides per year. In non-earthquake years, most landslides happen on south-facing slopes, facing the prevailing winds. In contrast, during or immediately after the earthquake, up to 32\% of the landslides occurred on north and northwest-facing slopes. Although we could not find imagery from the day after the earthquake, overview reconnaissance flights 10 and 16 days later showed that most of the landslides were recent, suggesting they were co-seismic.},
  language  = {en}
}
@article{ZhuPilzCotton2019,
  author    = {Zhu, Chuanbin and Pilz, Marco and Cotton, Fabrice},
  title     = {Which is a better proxy, site period or depth to bedrock, in modelling linear site response in addition to the average shear-wave velocity?},
  series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering},
  volume    = {18},
  journal   = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering},
  number    = {3},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1570-761X},
  doi       = {10.1007/s10518-019-00738-6},
  pages     = {797 -- 820},
  year      = {2019},
  abstract  = {This study aims to identify the best-performing site characterization proxy alternative and complementary to the conventional 30 m average shear-wave velocity V-S30, as well as the optimal combination of proxies in characterizing linear site response. Investigated proxies include T-0 (site fundamental period obtained from earthquake horizontal-to-vertical spectral ratios), V-Sz (measured average shear-wave velocities to depth z, z = 5, 10, 20 and 30 m), Z(0.8) and Z(1.0) (measured site depths to layers having shear-wave velocity 0.8 and 1.0 km/s, respectively), as well as Z(x-infer) (inferred site depths from a regional velocity model, x = 0.8 and 1.0, 1.5 and 2.5 km/s). To evaluate the performance of a site proxy or a combination, a total of 1840 surface-borehole recordings is selected from KiK-net database. Site amplifications are derived using surface-to-borehole response-, Fourier- and cross-spectral ratio techniques and then are compared across approaches. Next, the efficacies of 7 single-proxies and 11 proxy-pairs are quantified based on the site-to-site standard deviation of amplification residuals of observation about prediction using the proxy or the pair. Our results show that T-0 is the best-performing single-proxy among T-0, Z(0.8), Z(1.0) and V-Sz. Meanwhile, T-0 is also the best-performing proxy among T-0, Z(0.8), Z(1.0) and Z(x-infer) complementary to V-S30 in accounting for the residual amplification after V-S30-correction. Besides, T-0 alone can capture most of the site effects and should be utilized as the primary site indicator. Though (T-0, V-S30) is the best-performing proxy pair among (V-S30, T-0), (V-S30, Z(0.8)), (V-S30, Z(1.0)), (V-S30, Z(x-infer)) and (T-0, V-Sz), it is only slightly better than (T-0, V-S20). Considering both efficacy and engineering utility, the combination of T-0 (primary) and V-S20 (secondary) is recommended. Further study is needed to test the performances of various proxies on sites in deep sedimentary basins.},
  language  = {en}
}