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Catastrophic earthquake-induced landslides can occur on slopes composed of loosened and fractured rock masses. Although it is impossible to prevent such landslides, estimation of the susceptibility of slopes to earthquake-induced landslides is useful for risk management. An index of susceptibility to earthquake-induced landslides (ISEL) was developed by using helicopter-borne electromagnetic resistivity data. However, the ISEL has not yet been validated through the analysis of pre-earthquake data. In this study, ISEL values were estimated from resistivity and digital elevation data obtained in 2013 around Mt. Aso, Kyushu, before the 2016 Kumamoto earthquake. Although most of the landslides around Mt. Aso during the 2016 Kumamoto earthquake were mass movements of volcanic tephra layers, some of them occurred on loosened rock masses. Landslide susceptible areas at loosened rock masses are the target for ISEL value estimation. Our results validated the effectiveness of the ISEL as a predictor of earthquake-induced rock mass landslides.

3D coseismic deformation detected by remote sensing yields essential information for estimating the geometry and slip distribution of the causative fault. However, it is often difficult to be obtained by a single observation method due to data acquisition constraints. This study constructs a 3D coseismic deformation model of the 2011 Fukushima-ken Hamadori earthquake by integrating Differential Interferometric Synthetic Aperture Radar (DInSAR), and differential light detection and ranging (Dlidar) analyses. Both horizontal and vertical movements observed are almost consistent with those of the theoretical dislocation model of normal faulting. The fault displacements measured within ±45 m of the rupture based on the 3D deformation model is also in good agreement with the possible maximum field displacements. Fault dips and lateral displacement components are also harmonious with the field survey measurements. Dlidar detects full 3D motion, whereas the DInSAR detects deformations too small for the light detection and ranging (lidar). Combining the two products is helpful to produce a more robust 3D displacement field than possible from the lidar alone. [ABSTRACT FROM AUTHOR]

Detailed locations of surface ruptures and the distribution of deformation associated with large earthquakes offer insights to understand subsurface fault slip. We estimated the surface rupture traces and the distribution of near-fault offset during the 2014 Nagano earthquake in Japan (Mw 6.2) using pre- and postearthquake topographic data acquired by light detection and ranging (lidar) surveys. We conducted differential lidar (Dlidar) analysis based on the particle image velocimetry (PIV) method applied to the high-resolution 2013-2015 lidar dataset. The results show the 3D displacement (vertical and horizontal) due to the 2014 event and surface ruptures on the displacement map as clear contrast. The 2014 surface rupture zone is divided into the northern and the southern subsegments based on the surface offset distribution and geometry of the surface rupture. Moreover, we calculated the dip angles using the amount of vertical offset and horizontal contraction and estimated subsurface fault geometry of both subsegments. Furthermore, we detected broad (~1-2 km) horizontal contractions on the northern and southern extensions of surface ruptures, reflecting a deep part rupture. The surface rupture traces and vertical offset distribution from our analysis are consistent with the slip distribution from geodetic and seismological models; this fact ensures that the Dlidar analysis is useful for understanding the crustal movements in the future because of the increasing use of lidar data. [ABSTRACT FROM AUTHOR]