59 research outputs found

    Measuring velocities of a surge type glacier with SAR interferometry using ALOS-2 data

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    In recent years, in-situ measurements on Kongsvegen, a surge-type glacier located in the Kongsfjorden area, have showed an acceleration in the flow speeds of the glacier. This could indicate the onset of a surging event, which presents the opportunity to study the dynamics of a glacier surge using remote sensing techniques with in-situ data for reference. Synthetic aperture radar (SAR) is well suited for this, as it does not rely on the sun for illumination and is not obstructed by clouds. In addition, SAR can be used to measure displacement with high accuracy and resolution through the use of interferometric SAR (InSAR). This study investigates the acceleration of Kongsvegen using InSAR, MAI and offset tracking. Velocity measurements from the combination DInSAR - MAI are then compared to in-situ data as well as the offset tracking measurements. For image pairs where InSAR measurements are not possible due to phase decorrelation, offset tracking is attempted as a back-up. Data from 2015, 2018 and 2019 was available, and the evolution of flow speeds over time could therefore be evaluated. The image pairs from 2018-2019 were acquired with 14 days separation in time, while the 2015 image pairs were acquired with 28 and 42 days separation. Due to the longer separation in time, the 2015 image pairs decorrelated in time. In addition, a pair acquired in the summer of 2018 decorrelated as a result of surface melting on the glaciers. Therefore only 3 of the total 8 pairs available were suited for interferometric analysis. For the image pairs from 2018-2019, the InSAR measurements were in good agreement with the in-situ data, as they also indicated an acceleration of the flow speeds on Kongsvegen. The offset tracking results on these pairs overestimated the velocity magnitudes, but also showed an increase in time. Similar to the InSAR estimates, the offset tracking failed to produce reasonable results on the 2015 image pairs, likely because of the large temporal baseline and lack of surface features on Kongsvegen. Overall, InSAR could be used to measure flow speeds on Kongsvegen successfully, but more data with a short temporal baseline is needed for an in-depth analysis

    Ionospheric correction of interferometric SAR data with application to the cryospheric sciences

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    Thesis (Ph.D.) University of Alaska Fairbanks, 2018The ionosphere has been identified as an important error source for spaceborne Synthetic Aperture Radar (SAR) data and SAR Interferometry (InSAR), especially for low frequency SAR missions, operating, e.g., at L-band or P-band. Developing effective algorithms for the correction of ionospheric effects is still a developing and active topic of remote sensing research. The focus of this thesis is to develop robust and accurate techniques for ionospheric correction of SAR and InSAR data and evaluate the benefit of these techniques for cryospheric research fields such as glacier ice velocity tracking and permafrost deformation monitoring. As both topics are mostly concerned with high latitude areas where the ionosphere is often active and characterized by turbulence, ionospheric correction is particularly relevant for these applications. After an introduction to the research topic in Chapter 1, Chapter 2 will discuss open issues in ionospheric correction including processing issues related to baseline-induced spectrum shifts. The effect of large baseline on split spectrum InSAR technique has been thoroughly evaluated and effective solutions for compensating this effect are proposed. In addition, a multiple sub-band approach is proposed for increasing the algorithm robustness and accuracy. Selected case studies are shown with the purpose of demonstrating the performance of the developed algorithm. In Chapter 3, the developed ionospheric correction technology is applied to optimize InSAR-based ice velocity measurements over the big ice sheets in Greenland and the Antarctic. Selected case studies are presented to demonstrate and validate the effectiveness of the proposed correction algorithms for ice velocity applications. It is shown that the ionosphere signal can be larger than the actual glacier motion signal in the interior of Greenland and Antarctic, emphasizing the necessity for operational ionospheric correction. The case studies also show that the accuracy of ice velocity estimates was significantly improved once the developed ionospheric correction techniques were integrated into the data processing flow. We demonstrate that the proposed ionosphere correction outperforms the traditionally-used approaches such as the averaging of multi-temporal data and the removal of obviously affected data sets. For instance, it is shown that about one hundred multi-temporal ice velocity estimates would need to be averaged to achieve the estimation accuracy of a single ionosphere-corrected measurement. In Chapter 4, we evaluate the necessity and benefit of ionospheric-correction for L-band InSAR-based permafrost research. In permafrost zones, InSAR-based surface deformation measurements are used together with geophysical models to estimate permafrost parameters such as active layer thickness, soil ice content, and permafrost degradation. Accurate error correction is needed to avoid biases in the estimated parameters and their co-variance properties. Through statistical analyses of a large number of L-band InSAR data sets over Alaska, we show that ionospheric signal distortions, at different levels of magnitude, are present in almost every InSAR dataset acquired in permafrost-affected regions. We analyze the ionospheric correction performance that can be achieved in permafrost zones by statistically analyzing correction results for large number of InSAR data. We also investigate the impact of ionospheric correction on the performance of the two main InSAR approaches that are used in permafrost zones: (1) we show the importance of ionospheric correction for permafrost deformation estimation from discrete InSAR observations; (2) we demonstrate that ionospheric correction leads to significant improvements in the accuracy of time-series InSAR-based permafrost products. Chapter 5 summarizes the work conducted in this dissertation and proposes next steps in this field of research

    3-D Satellite Interferometry for Interseismic Velocity Fields

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    The global interseismic strain rate map is being accomplished rapidly with measurements of the space-based geodetic technique of InSAR. High-resolution measurements of crustal deformation from InSAR can provide crucial constraints on a region's active tectonics, geodynamics, and seismic hazard. However, space-based InSAR usually only provides good constraints on horizontal displacement in the east-west direction, with the north-south component typically provided by low-resolution GNSS measurements. Sentinel-1, on the other hand, has the potential to provide measurements that are sensitive to north-south motion, through exploitation of the burst overlap areas produced by the TOPS acquisition mode. However, the significant noise contributions from decorrelation and propagation through the ionosphere make it challenging to detect surface displacements associated with interseismic deformation needing millimeters per year accuracy. The ionospheric phase advance is a significant nuisance term that can bias InSAR measurements. Although methods have been developed to mitigate the effect, they are not always routinely applied when processing C-band SAR images, for which the effect is generally expected to be small. Nevertheless, the effect can be significant, especially when analyzing low deformation gradients over large areas using time-series analysis. Here, the work in Chapter 3 presents a time-series approach to ionospheric noise mitigation, which improves on existing methods. Firstly, I estimate the ionospheric contribution for each individual acquisition from multiple interferograms, which reduces noise. Secondly, this work improved the identification of unwrapping errors, which can bias the estimation. Thirdly, I introduce a new filtering approach, which gives better results, particularly at image edges and areas with variable density of coherent measurements. Furthermore, the approach is applicable when estimating along-track motion in burst overlap areas. The results show that applying the correction improves velocity accuracy significantly for both conventional line-of-sight and burst overlap interferometry techniques. The application of measuring long-term tectonic signals that concentrate in the north-south component with millimeters per year accuracy is essential to constrain interseismic strain globally. In Chapter 4, I also demonstrate a time-series approach with the burst overlap interferometry appropriate for extracting subtle long-term displacements. The approach includes mitigation of ionospheric noise, and I investigate different filtering approaches to optimize the reduction of decorrelation noise. I present the mean ground velocity in the azimuth direction from data acquired between 2014 and 2019 along the West-Lut Fault, a north-south striking fault in eastern Iran. The chi-square statistic defines a good agreement between the results and independent GNSS measurements. Moreover, the denser coverage of the technique allows to detect the variation in strain accumulation between northern and southern segments of the fault, with our modeling indicating a variation of slip rate from 9.2±0.5 mm/yr in the south to 4.3±0.5 mm/yr in the north. With current efforts to use InSAR to constrain strain rates globally, along-track measurements can fill a crucial gap in north-south sensitivity. With the achievement of that the burst overlap InSAR technique can measure azimuth motions across a slowly deforming area where the surface displacements are concentrated in the north-south component, this results in that, in the TOPS burst overlap region, the number of observations for a ground displacement can reach 3-4 times with different observational components. Measurement redundancy allows for the decomposition of observed velocities into three-dimensional components. In Chapter 5, I apply InSAR observations to estimate a deformation across the Chaman fault in both line-of-sight and along-track components using images from ascending and descending passes. I demonstrate an inversion to estimate the decomposed velocities. The algorithm employs a sparse GNSS network across the region to transform InSAR velocities to the GNSS reference frame. The results show that constraining the long-wavelength signal across the InSAR observations using GNSS data can mitigate the long-wavelength ionospheric disturbance that remains in the observations. The variation in slip rates across the Chaman fault is depicted by two transect profiles. The mean velocity profile at latitude 31˚N, where the Chaman fault is the only tectonic structure to accommodate strain, is consistent with 10.4±0.4 mm/yr of slip rate derived from the interseismic modeling. The optimal fault slip rate to fit with the mean velocity of the southern profile at latitude 29˚N is 5.5±0.8 mm/yr across the Chaman fault and 15.5±0.9 mm/yr across the parallel fault (the Ghazaband fault). I also demonstrate the benefits of high temporal sampling of InSAR observations with TOPS acquisition mode to study time-dependent surface deformation. I present the evolution of fault creeps, including seismic and aseismic fault slip along the Chaman fault during 2014-2018

    Toward Operational Compensation of Ionospheric Effects in SAR Interferograms: The Split-Spectrum Method

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    The differential ionospheric path delay is a major error source in L-band interferograms. It is superimposed to topography and ground deformation signals, hindering the measurement of geophysical processes. In this paper, we proceed toward the realization of an operational processor to compensate the ionospheric effects in interferograms. The processor should be robust and accurate to meet the scientific requirements for the measurement of geophysical processes, and it should be applicable on a global scale. An implementation of the split-spectrum method, which will be one element of the processor, is presented in detail, and its performance is analyzed. The method is based on the dispersive nature of the ionosphere and separates the ionospheric component of the interferometric phase from the nondispersive component related to topography, ground motion, and tropospheric path delay. We tested the method using various Advanced Land Observing Satellite Phased-Array type L-band synthetic aperture radar interferometric pairs with different characteristics: high to low coherence, moving and nonmoving terrains, with and without topography, and different ionosphere states. Ionospheric errors of almost 1 m have been corrected to a centimeter or a millimeter level. The results show how the method is able to systematically compensate the ionospheric phase in interferograms, with the expected accuracy, and can therefore be a valid element of the operational processor

    Synthetic Aperture Radar für Monitoring in städtischen Gebieten und im Bergbau

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    Considering it is hazardous to the environment and people, monitoring land movements at urban area become more and more significant. On the other hand, studying of land movements in non-urban area is also important. Synthetic aperture radar using interferometric technique, which is known as InSAR, is capable of providing a quite denser measurement over large areas. More specifically, Interferometric SAR (InSAR), Differential InSAR (DInSAR), Persistent Scatterers InSAR (PSI) techniques are developing to meet people¡¯s requirements of detecting land movements. Due to the different features of urban and non-urban area, the application of InSAR for land movements monitoring may come cross different challenges. D¨¹sseldorf was used as the urban test site by processing 20 TerraSAR-X images using PSI. Levelling results provided by the State Capital of D¨¹sseldorf validated the PSInSAR result, when two time series showed similar progress with very few discrepancies. Xishan mining region was chosen as the non-urban test site in this project, because of clear advantages. Such as well served mining schedule and literature and rapid movements with big phase gradients. In the experiments carried out in Xishan mine, InSAR fulfilled the aim of mining parameters derivation. GPS surveying was collated for the coordinates of corner reflectors, which can validate and improve the accuracy of geocoding (better than 5 m).Die Überwachung von Setzungen in städtischen Gebieten wird immer wichtiger, da es sich um eine potenzielle Bedrohung für die Umwelt und den Menschen handelt. Die Untersuchung von Landsenkungen in nicht-städtischen Bereichen sind ebenfalls sehr wichtig. Mit interferometrischen Auswertungen von Synthetic Aperture Radar Messungen (InSAR) ist man in der Lage große Bereiche hochauflösend zu beobachten. SAR Systeme können während des Tages, der Nacht und unter allen Wetterbedingungen arbeiten. Heutzutage gibt es zunehmendes Interesse an der Anwendung von SAR für das Monitoring von Veränderungen der Erdoberfläche. Hierzu wurden speziell die Techniken des Interferometrischen SAR (InSAR), Differential InSAR (DInSAR) und Persistent Scatterers InSAR (PSI) entwickelt. Aufgrund der unterschiedlichen Merkmale von urbanen und nichturbanen Gebieten, kann die Anwendung von InSAR für das Monitoring von Bewegungen unterschiedliche Herausforderungen stellen. Die Stadt Düsseldorf wurde als Testfeld für die Verarbeitung von 20 TerraSAR-X Bilder mit PSI ausgewählt. Die Ergebnisse aus dem Nivellement der Landeshauptstadt Düsseldorf wurden für die Validierung der PSInSAR Ergebnisse genutzt. Zwei Zeitreihen zeigen einen ähnlichen Verlauf mit sehr geringen Abweichungen. Die Bergbauregion Xishan wurde als nichturbanes Testgebiete in diesem Projekt ausgewählt, weil es die Möglichkeit bietet an Informationen über den Bergbau, die Zeitpläne und Literatur zu kommen und es dort schnelle Oberflächenbewegungen mit großen Phasengradienten gibt. Die durchgeführten Experimente im Xishan Gebiet zeigen, dass man mit der InSAR Auswertung auch Bergbauparameter ableiten kann. Für die Koordinatenbestimmung der Corner Reflektoren wurden GPS Messungen durchgeführt, die auch zur Verbesserung der Satellitenbasislinien dienen und die Genauigkeit der Geokodierung (kleiner 5 m) verbessern

    Advanced satellite radar interferometry for small-scale surface deformation detection

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    Synthetic aperture radar interferometry (InSAR) is a technique that enables generation of Digital Elevation Models (DEMs) and detection of surface motion at the centimetre level using radar signals transmitted from a satellite or an aeroplane. Deformation observations can be performed due to the fact that surface motion, caused by natural and human activities, generates a local phase shift in the resultant interferogram. The magnitude of surface deformation can be estimated directly as a fraction of the wavelength of the transmitted signal. Moreover, differential InSAR (DInSAR) eliminates the phase signal caused by relief to yield a differential interferogram in which the signature of surface deformation can be seen. Although InSAR applications are well established, the improvement of the interferometry technique and the quality of its products is highly desirable to further enhance its capabilities. The application of InSAR encounters problems due to noise in the interferometric phase measurement, caused by a number of decorrelation factors. In addition, the interferogram contains biases owing to satellite orbit errors and atmospheric heterogeneity These factors dramatically reduce the stlectiveness of radar interferometry in many applications, and, in particular, compromise detection and analysis of small-scale spatial deformations. The research presented in this thesis aim to apply radar interferometry processing to detect small-scale surface deformations, improve the quality of the interferometry products, determine the minimum and maximum detectable deformation gradient and enhance the analysis of the interferometric phase image. The quality of DEM and displacement maps can be improved by various methods at different processing levels. One of the methods is filtering of the interferometric phase.However, while filtering reduces noise in the interferogram, it does not necessarily enhance or recover the signal. Furthermore, the impact of the filter can significantly change the structure of the interferogram. A new adaptive radar interferogram filter has been developed and is presented herein. The filter is based on a modification to the Goldstein radar interferogram filter making the filter parameter dependent on coherence so that incoherent areas are filtered more than coherent areas. This modification minimises the loss of signal while still reducing the level of noise. A methodology leading to the creation of a functional model for determining minimum and maximum detectable deformation gradient, in terms of the coherence value, has been developed. The sets of representative deformation models have been simulated and the associated phase from these models has been introduced to real SAR data acquired by ERS-1/2 satellites. A number of cases of surface motion with varying magnitudes and spatial extent have been simulated. In each case, the resultant surface deformation has been compared with the 'true' surface deformation as defined by the deformation model. Based on those observations, the functional model has been developed. Finally, the extended analysis of the interferometric phase image using a wavelet approach is presented. The ability of a continuous wavelet transform to reveal the content of the wrapped phase interferogram, such as (i) discontinuities, (ii) extent of the deformation signal, and (iii) the magnitude of the deformation signal is examined. The results presented represent a preliminary study revealing the wavelet method as a promising technique for interferometric phase image analysis

    Glacier motion estimation using SAR offset-tracking procedures

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    Two image-to-image patch offset techniques for estimating feature motion between satellite synthetic aperture radar (SAR) images are discussed. Intensity tracking, based on patch intensity cross-correlation optimization, and coherence tracking, based on patch coherence optimization, are used to estimate the movement of glacier surfaces between two SAR images in both slant-range and azimuth direction. The accuracy and application range of the two methods are examined in the case of the surge of Monacobreen in Northern Svalbard between 1992 and 1996. Offset-tracking procedures of SAR images are an alternative to differential SAR interferometry for the estimation of glacier motion when differential SAR interferometry is limited by loss of coherence, i.e., in the case of rapid and incoherent flow and of large acquisition time intervals between the two SAR images. In addition, an offset-tracking procedure in the azimuth direction may be combined with differential SAR interferometry in the slant-range direction in order to retrieve a two-dimensional displacement map when SAR data of only one orbit configuration are available

    InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay

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    We quantify the bias and uncertainty of interferometric synthetic aperture radar (InSAR) displacement time series and their derivatives, the displacement velocities, by analyzing the systematic and stochastic components of the temporal variation of the tropospheric delay. The biases due to the systematic seasonal delay depend on the SAR acquisition times, whereas the uncertainties depend on the standard deviation of the random delay, the number of acquisitions, the total time span covered, and the covariance of the time series of the stochastic delay between a pixel and the reference. We study the contribution of the wet delay to the InSAR observations along the western India plate boundary using (i) Moderate Resolution Imaging Spectroradiometer precipitable water vapor, (ii) stratified tropospheric delay estimated from the ERA-I global atmospheric model, and (iii) seven Envisat InSAR swaths. Our analysis indicates that the amplitudes of the annual delay vary by up to ~10 cm in this region equivalent to a maximum displacement bias of ~24 cm in InSAR line of sight direction between two epochs (assuming Envisat IS6 beam mode). The stratified tropospheric delay correction mitigates this bias and reduces the scatter due to the stochastic delay. For ~7 years of Envisat acquisitions along the western India plate boundary, the uncertainty of the InSAR velocity field due to the residual stochastic wet delay after stratified tropospheric delay correction using the ERA-I model is in the order of ~2 mm/yr over 100 km and ~4 mm/yr over 400 km. We discuss the implication of the derived uncertainties on the full variance-covariance matrix of the InSAR data

    Tide model accuracy in the Amundsen Sea, Antarctica, from radar interferometry observations of ice shelf motion

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    This study assesses the accuracy of tide model predictions in the Amundsen Sea sector of West Antarctica. Tide model accuracy in this region is poorly constrained, yet tide models contribute to simulations of ocean heat transfer and to the removal of tidal signals from satellite observations of ice shelves. We use two satellite-based interferometric synthetic aperture radar (InSAR) methods to measure the tidal motion of the Dotson Ice Shelf at multiple epochs: a single-difference technique that measures tidal displacement and a double-difference technique that measures changes in tidal displacement. We use these observations to evaluate predictions from three tide models (TPXO7.1, CATS2008a-opt, and FES2004). All three models perform comparably well, exhibiting root-mean-square deviations from the observations of ∼9 cm (single-difference technique) and ∼10 cm (double-difference technique). Care should be taken in generalizing these error statistics because (1) the Dotson Ice Shelf experiences relatively small semidiurnal tides and (2) our observations are not sensitive to all tidal constituents. An error analysis of our InSAR-based methods indicates measurement errors of 7 and 4 cm for the single-and double-difference techniques, respectively. A model-based correction for the effect of fluctuations in atmospheric pressure yields an ∼6% improvement in the agreement between tide model predictions and observations. This study suggests that tide model accuracy in the Amundsen Sea is comparable to other Antarctic regions where tide models are better constrained. These methods can be used to evaluate tide models in other remote Antarctic waters
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