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

      Liao, Heming; Meyer, Franz J.; Freymueller, Jeffrey T.; Tape, Carl; Watkins, Brenton (2018-08)
      The 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.
    • Regional modeling of Greenland's outlet glaciers with the parallel ice sheet model

      Della-Giustina, Daniella N. (2011-12)
      The most recent report from the Intergovernmental Panel on Climate Change cites ice sheet dynamics as the greatest source of uncertainty for predicting current and future rates of sea level rise. This has prompted the development and use of ice sheet models that are capable of simulating the flow and evolution of ice sheets and their corresponding sea level contribution. In the Arctic, the Greenland ice sheet appears to be responding to a warming climate more quickly than expected. In order to determine sea level contribution from Greenland, it is necessary to capture the regional dynamics of the fast flowing outlet glaciers that drain the ice sheet. This work has developed a novel regional model capable of simulating an outlet glacier, and its associated drainage basin, as a mode of using the Parallel Ice Sheet Model. Specifically, it focuses on modeling the Jakobshavn Isbrae as a demonstration. The Jakobshavn Isbrae is one of the world's fastest flowing outlet glaciers, and accounts for nearly 5% of ice loss from the Greenland Ice Sheet. Additionally, the Jakobshavn Isbrae has been widely studied for several decades, and a wealth of remotely sensed and in situ data is available in this region. These data are used as model input and for model validation. We have completed a parameter study in this work to examine the behavior of the regional model. The purpose of this study was not to tune the model to match observations, but rather to look at the influence of parameter choices on the ice dynamics. Model results indicate that we have identified the subset of the model parameter space that is appropriate for modeling this outlet glacier. Additionally, we are able to produce some of this more interesting features that have been observed at Jakobshavn, such as the development and disintegration of a floating ice tongue and the distribution of observed surface velocities. We validate these model results by comparison with recent spatially rich measurements of ice surface speeds, as well as ice geometry.