The Haiyuan fault zone is a major discontinuity in the northeastern margin of the Tibetan plateau. A magnitude 8.5 earthquake occurred there in 1920. Both geological investigations and GPS measurements show that this fault zone is still highly active, with a slip rate of 3 to 10 mm/year , exhibiting a large range of variance in both space and time. We attempt to use the permanent scatterers interferometric (PSI) synthetic aperture radar technique to better detect the near-field motion of this fault zone. We process and analyze 38 scenes of ENVISAT/ASAR images from two neighboring descending orbits using the PSI method. The results show a remarkable velocity gradient of about 5 mm/year across the central segment of the fault zone and a rate of about 5 to 6 mm/year on its eastern segment. The motion senses are consistent with a left-lateral strike slip. The motion histories of most PS points show a stable linear variation trend in time series. In addition to these motion features that agree with those from geological, GPS and other observations, the dense PS analysis also reveals spatially continuous variations of crustal motion around the fault zone.
In order to discover the relationship between the earth surface deformation evolution and the water impoundment/discharge and penetration process in the Longtan Reservoir area, we process a time series of images from Envisat ASAR and ALOS PALSAR instruments using an MT-InSAR technique enhanced by corner reflectors. This allows us to successfully obtain a deformation map from this densely vegetated reservoir area with karst topography. We obtain time series of precise deformation images, which show clearly, for the first time, the complete spatio-temporal earth surface deformation evolution in the whole reservoir area during the impoundment/discharge process. The results from the two kinds of data show a similar underlying pattern: (1) The water load causes subsidence in almost all of its immediate surroundings; (2) the subsidence magnitude shows cyclic variation matching seasonal water level variation. Every year, the water level starts to increase in June and quickly reaches its peak in July to August, and the subsidence immediately follows and also reaches its peak magnitude in July to August; then the water level decreases slowly, and the area rebounds slowly. (3) Statistical analysis of time-series deformation shows that about 60% of the deformation occurs during the rain season (June to August) can be restored, and the remaining 40% become permanent.
We used the radar data from satellite ALOS/PALSAR of Japan and D-InSAR technology to derive the coseismic displacement produced by the Wenchuan, China Ms 8.0 earthquake on 12 May 2008. The result shows that the coseismic displacement primarily concentrated in a near-field range about 100km width on both sides of the Yingxiu-Beichuan fault. The incoherent zone about 250km long and 15~35km wide nearby the fault suffered the largest deformation with surface ruptures. The secondary deformed areas are 70km wide on each side of the incoherent zone, where the displacements exhibit a sunk northern wall with maximum -110~120cm and an uplifted southern wall with maximum 120~130cm, respectively. In the far-field range of the fault, displacements are less than 10cm. Using the offset tracking, we found clear rupture traces and coseismic displacement of 3m along the faults. With a model of four fault sections, we retrieved slip distribution on the faults. The inversion result reveals two slips of 10m at depths 5~20km beneath the Yingxiu-Beichuan fault and one slip of 2.3m at depth 5~20km below the Guanxian-Jiangyou fault, respectively. Thrust faulting dominates the southwestern Yingxiu-Beichuan fault and the entire Guanxian-Jiangyou fault, while right-slip is the primary component along the northeastern Yingxiu-Beichuan fault.
Atmospheric water vapor effects represents a major limitation to accuracy in InSAR applications. a method based on
GPS-ZWD timeseries and atmospheric transport model is developed to reproduce InSAR atmospheric signal so as to be
applied to reduce atmospheric effects in interferogram. Firstly, based on correlation between wator vapor effect and
topography, topography-dependent component of delay variation can be estimated by fitting a model of the vertical
profile of neutral atmospheric delay to the GPS ZWD measurements at the SAR overpass time, then we use the fitting
model and a SRTM DEM of imaged area to generate a map of altitude-dependent ZWD delay difference, which can be
used to reduce topography-dependent atmospheric phase in InSAR interferogram. After removing the
topography-dependent model, the residual fluctuations can be interpreted as turbulent variations of water vapor.
Atmospheric transport model is introduced to transform GPS-ZWD timeseries around SAR overpass time into a spatially
denser network of GPS-ZWD control points. The denser network of GPS-ZWD enable estimation of ZWD difference
maps that better match the turbulently-mixed atmospheric phase distortions observed in the InSAR data. Experimental
data analysis showed the method to seperately consider topography-dependent and turbulent mixing atmospheric effects
effectively reproduce atmospheric signal in InSAR interferogram.
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