Qian Sun

Kalman-Filter-Based Approach for Multisensor, Multitrack, and Multitemporal InSAR

A Kalman-filter-based approach is presented for resolving 3-D surface displacements using multisensor, multitrack, and multitemporal interferometric synthetic aperture radar (SAR) measurements. Measurements from each interferogram are projected into the three reference directions and combined in the Kalman filter model with displacements determined from previous interferograms to produce updated displacement measurements. Both simulated and real data sets are used to test the proposed approach. It is found that the method works well when the measurement noise is low. The displacements in the north direction, however, are much lower in accuracy than those in the other two directions and even become unstable when the measurement noise is high due to the polar-orbiting imaging geometries of the current satellite SAR sensors.

Three-Dimensional Surface Displacements From InSAR and GPS Measurements With Variance Component Estimation

Previous approaches that integrate interferometric synthetic aperture radar (InSAR) and GPS measurements for 3-D surface displacement mapping require statistically estimating the variances of the measurements to yield optimal results. We present a variance component estimation approach to weigh the InSAR and GPS measurements in deriving 3-D surface displacements. The approach exploits the observations themselves for determining the weighting scheme, and therefore the a priori information on the stochastic model of the observations is not required. This is of great importance as accurate knowledge on the stochastic model is often unavailable. The performance of the proposed method is validated with both simulated and real datasets.

Correcting ionospheric effects and monitoring two-dimensional displacement fields with multiple-aperture InSAR technology with application to the Yushu earthquake

Differential synthetic aperture radar interferometry (D-InSAR) can only measure one-dimensional surface displacements along the line-of-sight (LOS) direction which greatly inhibits its development and application. In this paper, we introduce a novel approach to measuring two-dimensional (2-D) surface displacements by exploiting a single InSAR pair, which is called multi-aperture InSAR (MAI) technology. We study the effects of baseline errors and the ionosphere on MAI technology and develop a directional filter and interpolator to minimize the ionospheric effects. A PALSAR image pair covering the 2010 Yushu earthquake is used to estimate the 2-D displacement fields of the earthquake using the MAI approach. The experimental results show that MAI is superior to conventional Offset-Tracking and therefore has great potential in co-seismic displacement measurement and source parameter inversion.

Investigating the Ground Deformation and Source Model of the Yangbajing Geothermal Field in Tibet, China with the WLS InSAR Technique

Ground deformation contains important information that can be exploited to look into the dynamics of a geothermal system. In recent years, InSAR has manifested its strong power in the monitoring of ground deformation. In this paper, a multi-temporal InSAR algorithm, WLS InSAR, is employed to monitor and characterize the Yangbajing geothermal field in Tibet, China, using 51 ENVISAT/ASAR images acquired from two overlapping descending tracks. The results reveal that the WLS InSAR algorithm can suppress the adverse effects of seasonal oscillations, associated with the freezing-thawing cycle of the permafrost in the Qinghai-Tibet Plateau. Deformations of up to 2 cm/yr resulting from the exploitation of the geothermal resource have been detected in the southern part of the Yangbajing field between 2006 and 2010. A source model inversion of the subsurface geothermal fluids was carried out based on the elastic half-space theory using the accumulated deformations. It was found that most geothermal fluid loss has occurred in the southern part of the shallow reservoir as the pore space beneath the northern part of field was recharged by the ascending flow from the deep layers of the reservoir through well-developed faults in the region.

On the Accuracy of Topographic Residuals Retrieved by MTInSAR

Topographic residuals in differential interferometric synthetic aperture radar (InSAR) measurements are mainly caused by inaccurate external digital elevation model (DEM). Accurate separation of the phase component contributed by topographic residuals plays an important role in the retrieval of deformation time series from InSAR observations. Even though the residuals can be modeled and estimated in the framework of multitemporal SAR interferometry (MTInSAR), it is not clear what an optimal processing strategy is and how accurate the estimation can reach. We analyze here the factors that affect the accuracy of the retrieved DEM residuals by applying four commonly used MTInSAR methods in a series of simulated scenarios. The results indicate that besides the quality of interferometric observations, the thresholds of spatial and temporal baselines, the diversity of spatial baseline lengths, the connectivity of interferogram network, and improper deformation model also fluctuate the accuracy of the retrieved topographic residuals. According to these affecting factors, this paper sheds light on an optimal approach to reliably retrieve accurate topographic residuals under MTInSAR framework.

Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

Although the past few decades have witnessed the great development of Synthetic Aperture Radar Interferometry (InSAR) technology in the monitoring of landslides, such applications are limited by geometric distortions and ambiguity of 1D Line-Of-Sight (LOS) measurements, both of which are the fundamental weakness of InSAR. Integration of multi-sensor InSAR datasets has recently shown its great potential in breaking through the two limits. In this study, 16 ascending images from the Advanced Land Observing Satellite (ALOS) and 18 descending images from the Environmental Satellite (ENVISAT) have been integrated to characterize and to detect the slow-moving landslides in Zhouqu, China between 2008 and 2010. Geometric distortions are first mapped by using the imaging geometric parameters of the used SAR data and public Digital Elevation Model (DEM) data of Zhouqu, which allow the determination of the most appropriate data assembly for a particular slope. Subsequently, deformation rates along respective LOS directions of ALOS ascending and ENVISAT descending tracks are estimated by conducting InSAR time series analysis with a Temporarily Coherent Point (TCP)-InSAR algorithm. As indicated by the geometric distortion results, 3D deformation rates of the Xieliupo slope at the east bank of the Pai-lung River are finally reconstructed by joint exploiting of the LOS deformation rates from cross-heading datasets based on the surface–parallel flow assumption. It is revealed that the synergistic results of ALOS and ENVISAT datasets provide a more comprehensive understanding and monitoring of the slow-moving landslides in Zhouqu.

Characterizing sudden geo-hazards in mountainous areas by D-InSAR with an enhancement of topographic error correction

Differential interferometric synthetic aperture radar (D-InSAR) has been viewed as a promising technique in monitoring sudden geo-hazards (e.g., earthquake and landslide) in mountainous areas. However, the tough natural settings (e.g., steep slopes and vegetation) pose the D-InSAR technique to face many challenges. Among them, phase residuals induced by inaccurate topographic heights that can result in intolerable error have not been paid adequate attention. We present, in this paper, a new strategy of using D-InSAR measurements to characterize sudden geo-hazards with an emphasis on the correction of topographic errors. In the proposed strategy, a least squares model with an outlier detector is constructed to estimate the topographic errors from multi-baseline wrapped differential interferograms, and the error-prone phase unwrapping procedure is not needed. The new strategy is applied to the ALOS PALSAR images acquired for monitoring a giant mudslide occurred in Zhouqu County, China. After refining the topographic height originally from the inaccurate ASTER GDEM, notable improvements to the D-InSAR measurements can be clearly seen, which is helpful to better interpret the deformation signals associated with the mudslide event. It is observed that the Zhouqu mudslide had caused large ground movements in the Luojiayu and Sanyanyu groove valleys. In addition, we find that the Suoertou landslide has been experiencing moderate ground movements during the geologic event.

Estimation of 3-D Surface Displacement Based on InSAR and Deformation Modeling

A new approach is presented for mapping 3-D surface displacement caused by subsurface fluid volumetric change based on 1-D interferometric synthetic aperture radar (InSAR) line-of-sight measurements and surface deformation modeling. The relationship between surface deformation and source fluid volumetric change is modeled according to elastic half-space theory. A distinctive advantage of the proposed approach is that it effectively extends the capability of the sun-synchronous orbit side-looking synthetic aperture radar that has been essentially only able to measure 1-D displacements accurately or at most 2-D displacements when InSAR measurements from more than one orbit or platform are combined. Experimental studies are carried out with both simulated and real data sets to test the performance of the method. The results have demonstrated that the approach works very well.

Retrieving three-dimensional coseismic displacements of the 2008 Gaize, Tibet earthquake from multi-path interferometric phase analysis

In this paper, synthetic aperture radar (SAR) data from ENVISAT ASAR ascending, descending and ALOS PALSAR ascending orbits are collected to investigate the coseismic displacements of the Mw 6.4 earthquake occurred in Gaize, Tibet on January 9, 2008 and the Mw 5.9 aftershock on January 16, 2008. Two interferometric phase analysis techniques, i.e., D-InSAR and multi-aperture InSAR, are employed to process the SAR data, with which the displacement measurements along three different line-of-sight (LOS) and three different azimuth directions are retrieved, respectively. Complete three-dimensional (3-D) coseismic displacement fields caused by the earthquake are then resolved by integrating the obtained LOS and azimuth displacement measurements with a weighted least squares adjustment, whose distributions are conformed to the two north-northeast trending northwest-dipping normal faults detected in previous studies. Ground subsidence and uplift are observed in the hanging wall and footwall of the main fault, respectively, and the subsidence reaches its maximum in the hanging wall of the second fault as a superimposed result of the Gaize earthquake and its aftershock. Anti-symmetric horizontal movements are also detected during the seismic events, which move inward in the focal region, but outward at the marginal. The left-lateral motions near the main fault indicate a small striking slip component caused by the Gaize earthquake. Finally, we discuss the potential of applying the derived spatially continuous 3-D displacement fields to determine the high-resolution 3-D strain fields of the Gaize earthquake, which provide important knowledge for assessing the source mechanism.

A Method for Measuring 3-D Surface Deformations With InSAR Based on Strain Model and Variance Component Estimation

Interferometric synthetic aperture radar (InSAR) technique is a proven technique for measuring 3-D surface deformations by combining InSAR measurements from different techniques (i.e., differential InSAR, multiaperture InSAR, and pixel offset-tracking) and different tracks (i.e., ascending and descending) on a pixel-by-pixel basis. However, it is difficult to obtain the exact a priori variances or weights for such different kinds of InSAR measurements, resulting in inaccurate estimations of 3-D deformations. This paper proposes a method to retrieve 3-D deformations with InSAR by integrating the strain model and variance component estimation algorithm, which can exploit the spatial correlation of the adjacent points’ deformations and produce accurate weights for multiple InSAR measurements. The proposed method is assessed with both simulated and real data sets. The results have shown that the proposed method can accurately measure 3-D surface deformations associated with geohazards, and even those occurring in a transient or short-term period (e.g., earthquake and volcanic eruption). In the case study of the 2007 eruption of Kilauea Volcano (Hawai’i), improvements of 51.2%, 22.4%, and 18.5% have been achieved for the derived east, north, and up displacements, respectively, with respect to those derived from the classical weighted least squares method.