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Summary of Proposal GEO1850

TitleStudy on the geometry and tectonics of Yadong-Gulu rift(Tibet) by TSX and GPS measurements
Investigator Xuejun, Qiao - Institute of Seismology,China Earthquake Administration, Geodesy
Team MemberNo team members defined
SummaryMethodologyGPS Profile cross main faults in YGR ①EW profile 1 across Nianqingtanggula southeastern pediment fault ②EW profile 2 across Nianqingtanggula southeastern pediment fault ③NS profile 1 across Yaluzangbu suture ④EW profile across YGR The total GPS site for above profiles are about 54 and will be surveyed two times SAR data Collection of involved area Data processing and the analysis of velocity field ①GPS data processing. GIPSY software will be used to process all the GPS data. ② InSAR data processing ROI_PAC and StaMPS software will be used to process all the SAR data. SBAS DinSAR will be applied to get the interseismic deformation map. We will use the JPL/Caltech ROI_PAC3.0 software to process the raw SAR images by using a 3-arc second SRTM DEM to remove the topographic phase component.Interferograms are downsampled using 4 looks in range and 20 looks in azimuth. A weighted power spectrum technique is applied to filter the fringes (Goldstein and Werner, 1998) to produce the wrapped interferograms shown in Figure 2, each with a centre scene incidence angle of 23. SNAPHU software is used in phase unwrapping. The unwrapped interferograms are geocoded to a geographic coordinate system and then converted to LOS (line-of-sight) range changes. ③Integration of GPS and InSAR deformation vector The vector of GPS and InSAR results have different look direction, their relationship is as follows: We can use some special transform to deal with the above equation and expect to get a reasonable result Deformation simulation and analysis Analysis of the relationship between deformation field and strong earthquakesAlgorithm to be used InSAR error extinction The error sources of InSAR mainly include atmospheric delay, DEM error and satellite orbit uncertainty. Among them water vapor in the atmospheric delay contributes the most. ①Ground based GPS measurements will be used to derive atmospheric delay and applyied to InSAR caliberation ② MERIS data will be employed to Envisat InSAR to remove the possible atmospheric delay. ③ Stacking InSAR will be used to reduce the error. ④ PSInSAR ⑤ SBAS InSAR Integration of GPS and InSAR to obtain reliable fault slip models Assume is the ground surface displacement observed by GPS and InSAR and is the slip vector in fault plane. The relationship between and can be expressed as: = G(m)+ (1) Where G(m) is the Green function of the fault geometry parameters and is the observation errors. Equation (1) is used to invert for the slip vector of every fault segment. In order to ensure smooth and continuous slip on neighboring segments and avoid contradictory movements, the modeled result and GPS/InSAR observation have to satisfy the following condition. min[||G(m) -||2+β-2||▽||2] (2) Where || ||2 is the Euclid norm, G(m) -is the residual, β is a coefficient to control the smoothness of fault and consistency of fault slips. ▽is the Laplace operator to control the roughness of slip. For the study of fault lock depth, we will use the similar methods mentioned by Elliott et al (2008), Cavalie (2008) and Wang et al. (2009). Distinction between coseismic and interseismic deformation Because of the complex geological structures and frequent seismic events in the area, we need to use accurate fault models to simulate the coseismic deformation and remove any possible errors. Some special methods such as checkerboard grid test and Monte Carlo estimation will be used to achieve the best results.

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DLR 2004-2016