SAR interferometry and optical remote sensing for analysis of co-seismic deformation, source characteristics and mass wasting pattern of Lushan (China, April 2013) earthquake

摘要

Co-seismic deformation associated with the Lushan (China) earthquake that occurred along the southwestern segment of the Longmenshan Fault Zone (LFZ) on the 20th April 2013 has been estimated by differential interferometric SAR (DInSAR) technique using Radarsat-2 data. The Lushan earthquake resulted in the deformation of the Sichuan basin and the Longmenshan ranges in proximity to the LFZ. The line of sight (LOS) displacement values obtained from DInSAR technique mainly range between -4.0 cm to +3.0 cm. The western Sichuan basin shows oblique westward movement with predominant downward component in areas farther from LFZ and predominant westward component over the downward movement in areas closer to the source fault. Inversion modelling has been used to derive the seismic source characteristics from DInSAR derived deformation values using elastic dislocation source type. The linear inversion model converged at a double-fault source solution consisting of a deeper, steep, NW dipping fault plane-1 of 60 km x 16 km dimension and a shallower, gentle, NW dipping fault plane-2 of 60 km x 15 km dimension, with distributed slip values varying between 0 to 2.26m. These fault planes (fault planes-1 and -2) coincide with the Dachuan-Shuangshi fault and the buried Range Front Fault, respectively. The inversion model gives a moment magnitude of 6.81 and the geodetic moment of 2.07 x 10(19) Nm, comparable to those given in literature, derived using teleseismic body wave data. Thus DInSAR technique helped to quantify the co-seismic deformation and to retrieve the source characteristics from the estimated deformation values. The study also evaluated the distribution pattern of earthquake induced landslides (EIL) triggered fresh or re-activated during the Lushan earthquake and found that they show spatial association with the seismic source zone and also with various pre-conditioning factors of slope instability. (C) 2014 Elsevier B.V. All rights reserved.