Interferometric Synthetic Aperture Radar Images Research Articles

Dynamic deformation of Seguam Island, Alaska, 1992–2008, from multi-interferogram InSAR processing

We generated a time-series of ERS-1/2 and ENVISAT interferometric synthetic aperture radar (InSAR) images to study ground surface deformation at Seguam Island from 1992 to 2008. We used the small baseline subset (SBAS) technique to reduce artifacts associated with baseline uncertainties and atmospheric delay anomalies, and processed images from two adjacent tracks to validate our results. Seguam Island comprises the remnants of two late Quaternary calderas, one in the western caldera of the island and one in the eastern part of the island. The western caldera subsided at a constant rate of ~1.6cm/yr throughout the study period, while the eastern caldera experienced alternating periods of subsidence and uplift: ~5cm/year uplift during January 1993–October 1993 (stage 1), ~1.6cm/year subsidence during October 1993–November 1998 (stage 2), ~2.0cm/year uplift during November 1998–September 2000 (stage 3), ~1.4cm/year subsidence during September 2000–November 2005 (stage 4), and ~0.8cm/year uplift during November 2005–July 2007 (stage 5). Source modeling indicates a deflationary source less than 2km below sea level (BSL) beneath the western caldera and two sources beneath the eastern caldera: an inflationary source 2.5–6.0km BSL and a deflationary source less than 2km BSL. We suggest that uplift of the eastern caldera is driven by episodic intrusions of basaltic magma into a poroelastic reservoir 2.5–6.0km BSL beneath the caldera. Cooling and degassing of the reservoir between intrusions result in steady subsidence of the overlying surface. Although we found no evidence of magma intrusion beneath the western caldera during the study period, it is the site (Pyre Peak) of all historical eruptions on the island and therefore cooling and degassing of intrusions presumably contributes to subsidence there as well. Another likely subsidence mechanism in the western caldera is thermoelastic contraction of lava flows emplaced near Pyre Peak during several historical eruptions, most recently in 1977 and 1992–93.

Time-series deformation monitoring over mining regions with SAR intensity-based offset measurements

Underground mining can induce large vertical displacements that often lead to the loss of coherence in repeat-pass interferometric synthetic aperture radar (SAR) images. Using SAR intensity images, this paper employs the image offset tracking method to map SAR slant range changes due to ground deformation over areas of mining. The rationale of slant range offset measurement with respect to the vertical deformation is analysed and the prerequisite of applying the slant range offset method to monitor vertical deformation is discussed. Results from the slant range offset method are used to produce time-series of cumulative ground displacements via least square estimate. We use six Advanced Land Observation Satellite (ALOS)-Phased Array L-band SAR (PALSAR) images over two coalfields in Inner Mogolia, China, to illustrate the proposed method and its effectiveness. We achieve deformation measurements with a precision of ∼0.2 m, with the maximum vertical displacement over the mining sites reaching ∼4.5 m. Finally, we use time-series results to outline common features identified in mining-induced deformation. Our results are supported by in situ investigations.

Ionospheric Correction of SAR Interferograms by Multiple-Aperture Interferometry

Interferometric synthetic aperture radar (InSAR) is a powerful technique that precisely measures surface deformations at a fine spatial resolution over a large area. However, the accuracy of this technique is sometimes compromised by ionospheric path delays on radar signals, particularly with L- and P-band SAR systems. To avoid ionospheric effects from being misinterpreted as ground displacement, it is necessary to detect and correct their contributions to interferograms. In this paper, we propose an efficient method for ionospheric measurement and correction and validate its theoretical and experimental performance. The proposed method exploits the linear relationship between the multiple-aperture interferometry phase and the azimuth derivative of the ionospheric phase. Theoretical analysis shows that a total electron content (TEC) accuracy of less than <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$1.0 \times 10^{-4}$</tex></formula> TEC units can be achieved when more than 100 neighboring samples can be averaged (multilooked), and the coherence is 0.5. The regression analysis between the interferometric phase and the topographic height shows that the root-mean-square error can be improved by a factor of two after ionospheric correction. A 2-D Fourier spectral analysis indicates that the ionospheric wave pattern in the uncorrected power spectrum has disappeared in the power spectrum of the corrected interferogram. These results demonstrate that the proposed method can effectively remove ionospheric artifacts from an ionosphere-distorted InSAR image. Note that the method assumes that there is no appreciable surface displacement in the along-track dimension of the interferogram.

Multichannel interferometric SAR phase unwrapping using extended Kalman Smoother

Phase unwrapping (PU) is one of the key processing steps in reconstructing the digital elevation model (DEM) of a scene from interferometric synthetic aperture radar (InSAR) data. The PU problem entails the estimation of an absolute phase from observation of its noisy principal (wrapped) values. Recently, PU approaches based on Kalman filtering have proved their efficacy in tackling the PU problem even when strong discontinuities of the height profile and noisy data are involved. This paper presents a novel multichannel InSAR PU algorithm using several interferometric SAR images based on the extended Kalman filter. The proposed technique exploits the capability of the Kalman algorithm to simultaneously perform noise filtering, PU, and multi-sensor data fusion. The proposed method, even being a Bayesian estimator, optimally fuses height information coming from an additional maximum likelihood estimator (MLE) combining the benefits of both the Bayesian and the non-Bayesian approaches. The performance of the proposed algorithm has been tested on simulated interferometric images proving the effectiveness of the proposed method.

InSAR Local Co-Registration Method Assisted by Shape-From-Shading

Interferometric synthetic aperture radar (InSAR) is a useful technology to observe the earth topography. However, a synthetic aperture radar (SAR) interferogram usually includes a lot of rotational points, that is, singular points (SPs). SPs seriously affect the quality of generated digital elevation model (DEM). One of the dominant origins of the SPs is the local distortion in the co-registration of the master and slave images, which are the source of the interferogram. Previously, we proposed a local and fine co-registration method of the master and the slave using the number of SPs as the evaluation criterion (SPEC method). In this paper, we propose an improved version of the SPEC method which uses the shape-from-shading technique additionally for a better adjustment. In comparison to the conventional SPEC method, results indicate that the proposed technique improves the signal-to-noise ratio of the created DEM from InSAR images.

Pre-eruption deformation caused by dike intrusion beneath Kizimen volcano, Kamchatka, Russia, observed by InSAR

Interferometric synthetic aperture radar (InSAR) images reveal a pre-eruption deformation signal at Kizimen volcano, Kamchatka, Russia, where an ongoing eruption began in mid-November, 2010. The previous eruption of this basaltic andesite-to-dacite stratovolcano occurred in 1927–1928. InSAR images from both ascending and descending orbital passes of Envisat and ALOS PALSAR satellites show as much as 6cm of line-of-sight shortening from September 2008 to September 2010 in a broad area centered at Kizimen. About 20cm of opening of a nearly vertical dike provides an adequate fit to the surface deformation pattern. The model dike is approximately 14km long, 10km high, centered 13km beneath Kizimen, and strikes NE–SW. Time-series analysis of multi-temporal interferograms indicates that (1) intrusion started sometime between late 2008 and July 2009, (2) continued at a nearly constant rate, and (3) resulted in a volume expansion of 3.2×107m3 by September 2010, i.e., about two months before the onset of the 2010 eruption. Earthquakes located above the tip of the dike accompanied the intrusion. Eventually, magma pressure in the dike exceeded the confining strength of the host rock, triggering the 2010 eruption. Our results provide insight into the intrusion process that preceded an explosive eruption at a Pacific Rim stratovolcano following nearly a century of quiescence, and therefore have implications for monitoring and hazards assessment at similar volcanoes elsewhere.

High sidelobe effects on interferometric coherence for circular SAR imaging geometry

The coherence is a measure for the accuracy of the interferometric phase, and the synthetic aperture radar (SAR) interferometric coherence is affected by several sources of the decorrelation noise. For the circular SAR (CSAR) imaging geometry, the system response function is in the form of the Bessel function which brings a high sidelobe, and the high sidelobe of CSAR will be an important factor influencing the interferometric coherence. The effect of the high sidelobe on the coherence is analyzed and deduced. Based on the interferometric characteristics of the slight difference in the viewing angles and the potential pixel offset in the interferometric SAR (InSAR) images, a relation between the radar impulse response and the coherence loss function is derived. From the relational model, the coherence loss function due to the high sidelobe of CSAR is then deduced, and compared with that of the conventional SAR. It is shown that the high sidelobe of CSAR focusing signal will severely affect the baseline decorrelation and coregistration decorrelation. Simulation results confirm the theoretical analysis and quantitatively show the baseline and coregistration decorrelation degradation due to the high sidelobes of CSAR.

Experimental Study on the Atmospheric Delay Based on GPS, SAR Interferometry, and Numerical Weather Model Data

In this paper, we present the results of an experiment aiming to compare measurements of atmospheric delay by synthetic aperture radar (SAR) interferometry and GPS techniques to estimates by numerical weather prediction. Maps of the differential atmospheric delay are generated by processing a set of interferometric SAR images acquired by the ENVISAT-ASAR mission over the Lisbon region from April to November 2009. GPS measurements of the wet zenith delay are carried out over the same area, covering the time interval between the first and the last SAR acquisition. The Weather Research and Forecasting (WRF) model is used to model the atmospheric delay over the study area at about the same time of SAR acquisitions. The analysis of results gives hints to devise mitigation approaches of atmospheric artifacts in SAR interferometry applications.

Digital elevation model (DEM) generation using the SAR interferometry technique

The development of satellite technology is rapidly increasing the evolution of remote sensing. Satellite images give extensive useful information about the land structure that is easily manageable in the process of generating true, high-speed information which allows the forecasting of future environmental and urban planning. Remote sensing comprises active and passive systems. Passive sensors detect natural radiation that is emitted or reflected by the object or surrounding area being observed. Active systems which produce their own electromagnetic energy and their main properties are their ability of collecting data in nearly all atmospheric conditions, day or night. These systems are frequently used to generate a digital elevation model (DEM) because they cover large areas. DEM supplies essential data for applications that are concerned with the Earth’s surface and DEMs derived from survey data are accurate but very expensive and time consuming to create. However, the use of satellite remote sensing to provide images to generate a DEM is considered to be an efficient method of obtaining data. Interferometric Synthetic Aperture Radar (InSAR) is a new geodetic technique for determining earth topography. InSAR measurements are highly dense and they only give information in Line of Sight of Radar. In the study, interferograms were produced from the InSAR images taken by ERS satellites in 1992 and 2007 and we developed the methods to generate a DEM using the InSAR technique and present the results relating to Kayseri Province in Turkey. The accuracy of the DEM derived from the InSAR technique is evaluated in comparison with a reference DEM generated from contours in a topographical map.

Joint estimation of moving target reflectivity and velocity via AT-InSAR systems based on complex interferometric data

In this paper a technique for the joint estimation of the complex reflectivity and of the radial velocity of ground moving targets, by means of Along-Track Interferometric Synthetic Aperture Radar (AT-InSAR) systems, is presented. It is essentially based on statistical estimation techniques and exploits the complex interferometric SAR images, contrarily to other conventional AT-InSAR methods, which estimate the target radial velocity exploiting only the interferometric phases. The performances of the method are evaluated both for single baseline and for dual-baseline satellite systems, in terms of Cramer Rao Lower Bounds and of Root Mean Square Errors obtained in numerical experiments, with reference to all the target parameters to be estimated, which are the amplitude and phase of the target reflectivity and the target radial velocity. It is shown that for single baseline systems the obtained radial velocity estimation accuracy is comparable with the one achievable with AT-InSAR methods exploiting phase-only data, and is very high for high values of signal to clutter ratio. For dual-baseline systems, instead, the use of amplitude and phase data allows a performance significantly better than the one achievable exploiting phase-only data. Moreover, in the dual baseline case, high velocity estimation accuracy can be obtained also with lower signal to clutter ratios.

Comparison and Analysis of Permafrost Railway Subgrade Settlement Deformation Monitoring

Under inclement Qinghai-Tibet plateau environment, monitoring and analysis of railway subgrade deformation in plateau permafrost region has very important engineering significance for stability evaluation and safety management. In the paper, satellite interferometry was applied to measure subgrade deformation in the Beiluhe test site along the Qinghai-Tibet railway with gathered satellite interferometric SAR images. Based on the satellite-interferometry-derived data, the deformation characteristics of six points in different permafrost subgrades (the sliced rock embankment, the crushed rock embankment and railway bridge) along the Qinghai-Tibet railway were analyzed and compared. The analysis results show that settlement is the main behavior of railway subgrade deformation and the deformation amount of railway bridge is less than the sliced or the crushed rock embankment along the Qinghai-Tibet railway in permafrost regions.

Block adjustment of InSAR images based on the combination of F.Leberl and interferometric models

为解决西部测图中缺少控制点的问题，提出了一种新的干涉合成孔径雷达（InSAR）影像区域网平差方法.该方法将F.Leberl模型与干涉测量模型相结合，并采用交替趋近与LDL’稀疏矩阵分解技术求解大规模法方程.实验结果表明，与传统的基于F.Leberl模型的平差方法相比较，提出的方法精度更高.由于新模型中增加了三个定标参数，因此能够同时实现多航带幅度图像以及数字高程模型（DEM）的联合平差.最后结合实际机载InSAR系统参数对影响平差精度的因素进行了详细的分析.;为解决西部测图中缺少控制点的问题，提出了一种新的干涉合成孔径雷达（InSAR）影像区域网平差方法.该方法将F.Leberl模型与干涉测量模型相结合，并采用交替趋近与LDL’稀疏矩阵分解技术求解大规模法方程.实验结果表明，与传统的基于F.Leberl模型的平差方法相比较，提出的方法精度更高.由于新模型中增加了三个定标参数，因此能够同时实现多航带幅度图像以及数字高程模型（DEM）的联合平差.最后结合实际机载InSAR系统参数对影响平差精度的因素进行了详细的分析.

Generating a relative geologic time volume by 3D graph-cut phase unwrapping method with horizon and unconformity constraints

Construction of a relative geologic time (RGT) volume is vital to seismic geomorphological and sedimentological interpretation. Seismic instantaneous phase unwrapping provides an excellent approach for generating an RGT volume. Although several 2D or 3D seismic phase unwrapping results have been published, there is a clear need for discussions on concrete methods for seismic phase unwrapping. We have developed the graph-cut phase unwrapping method, which performs well in the interferometric synthetic aperture radar image processing. It has advantages of strong discontinuity-preserving ability and high computing efficiency. To make it suitable for 3D seismic phase unwrapping, the method is improved by extending it from 2D to 3D, and by introducing the seismic horizon and unconformity constraints. The strong and continuous conformable seismic events, which can be easily tracked by certain autopicking methods, are introduced as horizon constraints for guiding the phase unwrapping to ensure a constant unwrapped phase on a constraining horizon. This idea is based on the fact that continuous seismic horizons are of time-stratigraphic significance. The horizon constraints can promise a correct unwrapped result on the constraining horizons and avoid the possible phase unwrapping errors propagating across a horizon. An unconformity represents a geologic time discontinuity, which is difficult to recover in an RGT volume by phase unwrapping. What’s worse, incorrect phase unwrapping on an unconformity will result in some discontinuities of unwrapped phase in the conformable data areas outside the unconformity. Interpreted unconformities are used as unconformity constraints to recover the discontinuities of the unwrapped phase at the constraining unconformities. As a test, our improved 3D graph-cut phase unwrapping method is successfully applied to the late Permian to early Triassic carbonate reservoirs in northern Sichuan Basin, southwest China. The results match well with the regional geologic background.

On the accuracy of integrated water vapor observations and the potential for mitigating electromagnetic path delay error in InSAR

Abstract. A field campaign was carried out in the framework of the Mitigation of Electromagnetic Transmission errors induced by Atmospheric Water Vapour Effects (METAWAVE) project sponsored by the European Space Agency (ESA) to investigate the accuracy of currently available sources of atmospheric columnar integrated water vapor measurements. The METAWAVE campaign took place in Rome, Italy, for the 2-week period from 19 September to 4 October 2008. The collected dataset includes observations from ground-based microwave radiometers and Global Positioning System (GPS) receivers, from meteorological numerical model analysis and predictions, from balloon-borne in-situ radiosoundings, as well as from spaceborne infrared radiometers. These different sources of integrated water vapor (IWV) observations have been analyzed and compared to quantify the accuracy and investigate the potential for mitigating IWV-related electromagnetic path delay errors in Interferometric Synthetic Aperture Radar (InSAR) imaging. The results, which include a triple collocation analysis accounting for errors inherently present in every IWV measurements, are valid not only to InSAR but also to any other application involving water vapor sensing. The present analysis concludes that the requirements for mitigating the effects of turbulent water vapor component into InSAR are significantly higher than the accuracy of the instruments analyzed here. Nonetheless, information on the IWV vertical stratification from satellite observations, numerical models, and GPS receivers may provide valuable aid to suppress the long spatial wavelength (&gt;20 km) component of the atmospheric delay, and thus significantly improve the performances of InSAR phase unwrapping techniques.

A novel system parameters design and performance analysis method for Distributed Satellite-borne SAR system

As a promising new technology emerged in recent years, the Distributed Satellite-borne SAR (DSS) system with Interferometric Synthetic Aperture Radar (InSAR) imaging capability has been recognized by the remote sensing community as an integrated part of the spaceborne earth observation system. However, most researches on DSS were focused on individual aspects of system design/analysis and data processing, while few studies have been dedicated to establishing a standard methodological framework for universal DSS system design. Aiming at this problem, the topics of DSS system error analysis and design method are investigated in this paper. Firstly, a rigorous error propagation model of height measurement is theoretically derived from the DSS InSAR imaging geometry, and the impact of each error sources in this model on the height measurement accuracy is analyzed individually. In particular, the baseline length and its measurement error in the InSAR imaging plane are identified as the dominant factors. Second, a new method for DSS system design is proposed based on our analyses with the error propagation model. This method consists of two important phases, namely collaboration design and monostatic design. The major objective of collaboration design is to determine the configuration and parameters for the coordination between satellites in the DSS system. Afterwards, the key parameters for single satellite and the payload are determined by the monostatic design. Thirdly, a system performance analysis method is developed to comprehensively evaluate the performance of the pre-designed DSS system. In the next section, a typical example of DSS system design is given to demonstrate the effectiveness of the proposed system design and analysis methods. The target DSS system has the same goal and hardware configuration as the TanDEM-X mission. Finally, the conclusion is drawn with our major findings are presented.

Ionospheric Artifacts in Simultaneous L-Band InSAR and GPS Observations

Phase artifacts in interferometric synthetic aperture radar (InSAR) images frequently degrade the interpretability of the phase and correlation signatures of terrain. Often, these distortions are attributed to spatially variable ionospheric propagation delays at two different SAR acquisition times. We present here L-band InSAR data from Iceland, California, and Hawaii. The California and Hawaii interferograms show no significant ionospheric artifacts, while the Iceland interferogram shows a maximum misregistration of three pixels in the azimuth direction, which leads to severe phase decorrelation artifacts in the InSAR image. We relate the misregistration of complex pixels seen in the interferograms to the gradient of the ionospheric total electron content (TEC) observed by global positioning system (GPS) data and confirm that indeed the phase artifacts in the Iceland interferogram are due to dispersive ionospheric propagation rather than other decorrelation factors such as neutral atmospheric delays. We develop a method to measure the spatial TEC variation at synthetic aperture length scales using dual-frequency GPS carrier phase data. We solve for the GPS data ambiguities using a low-resolution ionosphere reference derived from either available ionospheric observations or the GPS carrier phase data themselves. GPS observations show directly the level of ionospheric variability, and the spatial TEC gradient as observed by GPS predicts the misregistration of complex pixels in interferograms in all three areas. This confirmation of the cause of the image artifacts suggests that they can be routinely corrected from the InSAR data alone, provided that the sensor measures the change in TEC along the radar swath.

A Fast Offset Estimation Approach for InSAR Image Subpixel Registration

A fast offset estimation approach for interferometric synthetic aperture radar (InSAR) image pair subpixel registration is proposed for cases of relatively gentle topography and/or short baseline. A coarse-to-fine registration strategy is taken. The pixel-level offset is estimated in the coarse registration step by a fast feature-based estimation, which uses the speeded up robust feature operator and fast least trimmed squares (Fast-LTS) estimator to accelerate the feature extraction and parameter estimation. A fine registration is performed subsequently. The conventional normalized cross-correlation algorithm (NCCA) searches for the optimal subpixel offset by oversampling either the coarse cross correlation or the InSAR image patch pair. The offset estimation accuracy is restricted by the oversampling rate, and the computational burden is heavy when high accuracy is demanded. In this letter, we transform the oversampling and correlation searching process of NCCA into a nonlinear optimization problem, which takes the maximization of the coherent cross correlation as the objective function; by solving it, the subpixel offset can be fast and exactly obtained without any image oversampling. The final registration parameters are inverted by Fast-LTS fitting of a series of subpixel tie point correspondences which can be constructed after applying the approach to several image patch pairs. RadarSat-2 data are used to test the approach, and the results show that it performs very well not only on the speed but also on the accuracy.

Unsupervised Classification of PolInSAR Data Based on Shannon Entropy Characterization With Iterative Optimization

In this paper, we propose a modified unsupervised classification method for the analysis of polarimetric and interferometric synthetic aperture radar (PolInSAR) images using the intensity, polarimetric and interferometric contributions to the Shannon entropy characterization. In order to improve the classification accuracy where the polarimetric information is similar, the method gives intensity, polarimetric and interferometric information equal weighting to more effectively use the full range of information contained in PolInSAR data. In addition, this method uses an iterative clustering scheme which combines the expectation maximization (EM) and fast primal-dual (FastPD) optimization techniques to improve the classification quality. The first step of the method is to extract the Shannon entropy characterization from the PolInSAR data. Then, the image is initially classified respectively by the spans of the intensity, polarimetric and interferometric contributions to Shannon entropy. Finally, classification results of different contributions are merged and reduced to a specified number of clusters. An iterative clustering scheme is applied to further improve the classification results. The effectiveness of this method is demonstrated with DLR (German Aerospace Center) E-SAR PolInSAR data and CETC (China Electronics Technology Group Corporation) 38 Institute PolInSAR data.

Can spaceborne SAR interferometry be used to study the temporal evolution of PWV?

In this work we investigate the use of Synthetic Aperture Radar (SAR) interferometry (InSAR) to generate maps of temporal variations of the Precipitable Water Vapor (PWV) spatial distribution with a horizontal resolution as fine as 10÷20m depending on the radar wavelength, and over a swath typically 100km wide. We present the result of a time series of PWV maps obtained by processing a set of interferometric SAR images acquired by the ENVISAT-ASAR mission over the Lisbon region from November 2008 to November 2009. Maps are calibrated by means of GPS measurements of the PWV over the same area and covering the time interval between the first and last SAR acquisition. Current interferometric spaceborne missions, which can also be used to generate PWV maps, relies on SAR sensors working at different frequency bands: L (ALOS-PALSAR), C (ENVISAT-ASAR, RADARSAT) and X (TerraSAR-X, Cosmo-Sky-Med) and with a repetition cycle ranging from 11 (TerraSAR-X and Cosmo-Sky-Med) to 46days (ALOS-PALSAR). The precision of these maps can be smaller than 1mm depending on the radar wavelength and the spatial filtering. We also demonstrate that the merging of PWV maps obtained by processing time series of interferometric SAR images acquired from different tracks of the same satellite and/or different spaceborne missions gives information about the temporal evolution of the PWV spatial distribution with a sampling period of a few days, much shorter than the revisiting times of each SAR sensor. The availability of such PWV maps could increase the quality of quantitative precipitation forecasting and open interesting perspectives for nowcasting applications.

Preliminary Result of Permafrost Roadbed Settlement Measurement Using Satellite D-InSAR Technology

Monitoring ground subsidence of roadbed in permafrost region is very important for stability evaluation and safety management. To test its applicability to deformation monitoring for railway subgrade settlement in plateau permafrost region, satellite differential interferometric synthetic aperture radar technology (D-InSAR) has been applied to detect subgrade deformation in one test site along the Qinghai-Tibet railway with gathered interferometric SAR images. The preliminary experimental results showed that satellite D-InSAR technology can effectively acquire long-time deformation sequence through analyzing the ground scatterers with relative stable phase and are in accordance with the results obtained by conventional in-situ ground leveling. Along the Qinghai-Tibet railway in permafrost regions, it is found that settlement is the main behavior of subgrade deformation and the deformation amount of railway bridge is less than the sliced or the crushed rock embankment. It has very important engineering significance for state key infrastructure long-term monitoring system in plateau permafrost region.