This thesis considers the use of Interferometric Synthetic Aperture Radar (InSAR) for surveying temporal fluctuations in the velocity of glaciers in the Arctic region. The aim of this thesis is to gain a broader understanding of the manner in which the flow of both land- and marine-terminating glaciers varies over time, and to asses the ability of InSAR to resolve flow changes over timescales which provide useful information about the physical processes that control them. InSAR makes use of the electromagnetic phase difference between successive SAR images to produce interference patterns (interferograms) which contain information on the topography and motion of the Earth's surface in the direction of the radar line-of-sight. We apply established InSAR techniques (Goldstein et al., 1993) to (i) the 925 km2 LangjÖkull Ice Cap (LIC) in Iceland, which terminates on land (ii) the 8 500 km2 Flade Isblink Icecap (FIIC) in Northeast Greenland which has both land- and marine-terminating glaciers and (iii) to a 7 000 km2 land-terminating sector of the Western Greenland Ice Sheet (GrIS). It is found that these three regions exhibit velocity variations over contrasting timescales. At the LIC, we use an existing ice surface elevation model and dual-look SAR data acquired by the European Remote Sensing (ERS) satellite to estimate ice velocity (Joughin et al., 1998) during late-February in 1994. A comparison with direct velocity measurements determined by global positioning system (GPS) sensors during the summer of 2001 shows agreement (r2 = 0.86), suggesting that the LIC exhibits moderate seasonal and inter-annual variations in ice flow. At the FIIC, we difference pairs of interferograms (Kwok and Fahnestock, 1996) formed using ERS SAR data acquired between 15th August 1995 and 3rd February 1996 to estimate ice velocity on four separate days. We observe that the flow of 5 of the 8 outlet glaciers varies in latesummer compared with winter, although flow speeds vary by up to 20 % over a 10 day period in August 1995. At the GrIS, we use InSAR (Joughin et al., 1996) and ERS SAR data to reveal a detailed pattern of seasonal velocity variations, with ice speeds in latesummer up to three times greater than wintertime rates. We show that the degree of seasonal speedup is spatially variable and correlated with modeled runoff, suggesting that seasonal velocity changes are controlled by the routing of water melted at the ice sheet surface. The overall conclusion of this work is that the technique of InSAR can provide useful information on fluctuations in ice speed across a range of timescales. Although some ice masses exhibit little or no temporal flow variability, others show marked inter-annual, seasonal and even daily variations in speed. We observe variations in seasonality in ice flow over distances of ~ 10 km and over time periods of ~10 days during late-summer. With the aid of ancillary meteorological data, we are able to establish that rates of flow in western Greenland are strongly moderated by the degree of surface melting, which varies seasonally and secularly. Although the sampling of our data is insufficiently frequent and spans too brief a period for us to derive a general relationship between climate and seasonality of flow, we show that production of meltwater at the ice surface and its delivery to the ice bed play an important role in the modulation of horizontal flow speeds. We suggest that a similarly detailed investigation of other ice masses is required to reduce the uncertainty in predictions of the future Arctic land-ice contribution to sea level in a warming world.

Interferometric Synthetic Aperture Radar (InSAR) is an established technique which has been applied to Earth surface displacement analysis and topographic reconstruction. Two complex coherent SAR acquisitions of the same scene are combined to form an interferogram from which surface displacement or terrain measurements are made. The similarities between both SAR signals is captured in the coherence and its magnitude is determined by the spatial separation between acquiring antennas and the changes (if any) to the physical characteristics of the scattering target in the duration between both SAR acquisitions. Both of these products derivable from the interferometric process have been applied in this study with the aim of enhancing monitoring and assessing changes in the coastal environment, with emphasis on the coastal geomorphology. A combination of remote sensing data acquired for Montrose Bay, NE Scotland, has been used to analyze changes to the geomorphology of the beach and dune system in terms of sediment volume analysis, erosion and accretion processes and shoreline changes over a short-term period of 4 years. The interferometric coherence was applied to detect changes to the dune morphology, which have been actively eroding at the southern flank of the Bay. The interferometric analysis presented in this thesis was based on SAR data acquired by the Sentinel-1 SAR antenna and the results demonstrated the limitations of the sensor for terrain mapping and DEM reconstruction. In addition, the significance of the vegetation on the interferometric coherence was demonstrated. However, the results have shown that temporal baseline remained a significant consideration in the application of interferometric coherence in highly dynamic environments such as the coastal environment.

Volcanic subsidence, caused by partial emptying of magma in the subsurface reservoir has long been observed by spaceborne radar interferometry. Monitoring long-term crustal deformation at the most notable type of volcanic subsidence, caldera, gives us insights of the spatial and hazard-related information of subsurface reservoir. Several subsiding calderas, such as volcanoes on the Galapagos islands have shown a complex ground deformation pattern, which is often composed of a broad deflation signal affecting the entire edifice and a localized subsidence signal focused within the caldera floor. Although numerical or analytical models with multiple reservoirs are proposed as the interpretation, geologically and geophysically evidenced ring structures in the subsurface are often ignored. Therefore, it is still debatable how deep mechanisms relate to the observed deformation patterns near the surface. We aim to understand what kind of activities can lead to the complex deformation. Using two complementary approaches, we study the three-dimensional geometry and kinematics of deflation processes evolving from initial subsidence to later collapse of calderas. Firstly, the analog experiments analyzed by structure-from-motion photogrammetry (SfM) and particle image velocimetry (PIV) helps us to relate the surface deformation to the in-depth structures. Secondly, the numerical modeling using boundary element method (BEM) simulates the characteristic deformation patterns caused by a sill-like source and a ring-fault. Our results show that the volcano-wide broad deflation is primarily caused by the emptying of the deep magma reservoir, whereas the localized deformation on the caldera floor is related to ring-faulting at a shallower depth. The architecture of the ring-fault to a large extent determines the deformation localization on the surface. Since series evidence for ring-faulting at several volcanoes are provided, we highlight that it is vital to include ring-fault activity in numerical or analytical deformation source formulation. Ignoring the process of ring-faulting in models by using multiple point sources for various magma reservoirs will result in erroneous, thus meaningless estimates of depth and volume change of the magmatic reservoir(s).

Mapping of earth resources, environmental monitoring, and many other systems require high-resolution wide-area imaging. Since images often have to be captured at night or in inclement weather conditions, a capability is provided by Synthetic Aperture Radar (SAR). SAR systems exploit radar signal's long-range propagation and utilize digital electronics to process complex information, all of which enables high-resolution imagery. This gives SAR systems advantages over optical imaging systems, since, unlike optical imaging, SAR is effective at any time of day and in any weather conditions. Moreover, advanced technology called Interferometric Synthetic Aperture Radar (InSAR), has the potential to apply phase information from SAR images and to measure ground surface deformation. However, given the current state of technology, the quality of InSAR data can be distorted by several factors, such as image co-registration, interferogram generation, phase unwrapping, and geocoding. Image co-registration aligns two or more images so that the same pixel in each image corresponds to the same point of the target scene. Super-Resolution (SR), on the other hand, is the process of generating high-resolution (HR) images from a low-resolution (LR) one. SR influences the co-registration quality and therefore could potentially be used to enhance later stages of SAR image processing. Our research resulted in two major contributions towards the enhancement of SAR processing. The first one is a new learning-based SR model that can be applied with SAR, and similar applications. A second major contribution is utilizing the devised model for improving SAR co-registration and InSAR interferogram generation, together with methods for evaluating the quality of the resulting images. In the case of phase unwrapping, the process of recovering unambiguous phase values from a two-dimensional array of phase values known only modulo $2\pi$ rad, our research produced a third major contribution. This third major contribution is the finding that quantum annealers can resolve problems associated with phase unwrapping. Even though other potential solutions to this problem do currently exist - based on network programming for example - network programming techniques do not scale well to larger images. We were able to formulate the phase unwrapping problem as a quadratic unconstrained binary optimization (QUBO) problem, which can be solved using a quantum annealer. Since quantum annealers are limited in the number of qubits they can process, currently available quantum annealers do not have the capacity to process large SAR images. To resolve this limitation, we developed a novel method of recursively partitioning the image, then recursively unwrapping each partition, until the whole image becomes unwrapped. We tested our new approach with various software-based QUBO solvers and various images, both synthetic and real. We also experimented with a D-Wave Systems quantum annealer, the first and only commercial supplier of quantum annealers, and we developed an embedding method to map the problem to the D-Wave 2000Q_6, which improved the result images significantly. With our method, we were able to achieve high-quality solutions, comparable to state-of-the-art phase-unwrapping solvers. / Graduate

Satellite geodesy plays an important role in earth observation. This dissertation presents three applications of satellite geodesy in environmental and climate change. Three satellite geodesy techniques are used: high-precision Global Positioning System (GPS), the Gravity Recovery and Climate Experiment (GRACE) and Interferometric Synthetic Aperture Radar (InSAR). In the first study, I use coastal uplift observed by GPS to study the annual changes in mass loss of the Greenland ice sheet. The data show both spatial and temporal variations of coastal ice mass loss and suggest that a combination of warm atmospheric and oceanic condition drove these variations. In the second study, I use GRACE monthly gravity change estimates to constrain recent freshwater flux from Greenland. The data show that Arctic freshwater flux started to increase rapidly in the mid-late 1990s, coincident with a decrease in the formation of dense Labrador Sea Water, a key component of the deep southward return flow od the Atlantic Meridional Overturning Circulation (AMOC). Recent freshening of the polar oceans may be reducing formation of Labrador Sea Water and hence may be weakening the AMOC. In the third study, I use InSAR to monitor ground deformation caused by CO2 injection at an enhanced oil recovery site in west Texas. Carbon capture and storage can reduce CO2 emitted from power plants, and is a promising way to mitigate anthropogenic warming. From 2007 to 2011, ~24 million tons of CO2 were sequestered in this field, causing up to 10 MPa pressure buildup in a reservoir at depth, and surface uplift up to 10 cm. This study suggests that surface displacement observed by InSAR is a cost-effective way to estimate reservoir pressure change and monitor the fate of injected fluids at waste disposal and CO2 injection sites.