Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

Constraining Source Models, Underlying Mechanisms, and Hazards Associated with Slow Slip Events: Insight from Space-Borne Geodesy and Seismology

abstract: The movement between tectonic plates is accommodated through brittle (elastic) displacement on the plate boundary faults and ductile permanent deformation on the fault borderland. The elastic displacement along the fault can occur in the form of either large seismic events or aseismic slip, known as fault creep. Fault creep mainly occurs at the deep ductile portion of the crust, where the temperature is high. Nonetheless, aseismic creep can also occur on the shallow brittle portion of the fault segments that are characterized by frictionally weak material, elevated pore fluid pressure, or geometrical complexity. Creeping segments are assumed to safely release the accumulated strain(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992)(Kodaira et al., 2004; Rice, 1992) on the fault and also impede propagation of the seismic rupture. The rate of aseismic slip on creeping faults, however, might not be steady in time and instead consist of successive periods of acceleration and deceleration, known as slow slip events (SSEs). SSEs, which aseismically release the strain energy over a period of days to months, rather than the seconds to minutes characteristic of a typical earthquake, have been interpreted as earthquake precursors and as possible triggering factor for major earthquakes. Therefore, understanding the partitioning of seismic and aseismic fault slip and evolution of creep is fundamental to constraining the fault earthquake potential and improving operational seismic hazard models. Thanks to advances in tectonic geodesy, it is now possible to detect the fault movement in high spatiotemporal resolution and develop kinematic models of the creep evolution on the fault to determine the budget of seismic and aseismic slip. In this dissertation, I measure the decades-long time evolution of fault-related crustal deformation along the San Andrea Fault in California and the northeast Japan subduction zone using space-borne geodetic techniques, such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR). The surface observation of deformation combined with seismic data set allow constraining the time series of creep distribution on the fault surface at seismogenic depth. The obtained time-dependent kinematic models reveal that creep in both study areas evolves through a series of SSEs, each lasting for several months. Using physics-based models informed by laboratory experiments, I show that the transient elevation of pore fluid pressure is the driving mechanism of SSEs. I further investigate the link between SSEs and evolution of seismicity on neighboring locked segments, which has implications for seismic hazard models and also provides insights into the pattern of microstructure on the fault surface. I conclude that while creeping segments act as seismic rupture barriers, SSEs on these zones might promote seismicity on adjacent seismogenic segments, thus change the short-term earthquake forecast.Dissertation/ThesisDoctoral Dissertation Geological Sciences 201

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under Project TEC2011-28201-C02-02 and in part by the Generalitat Valenciana under Project ACOMP/2014/136

Geodetic monitoring of complex shaped infrastructures using Ground-Based InSAR

In the context of climate change, alternatives to fossil energies need to be used as much as possible to produce electricity. Hydroelectric power generation through the utilisation of dams stands out as an exemplar of highly effective methodologies in this endeavour. Various monitoring sensors can be installed with different characteristics w.r.t. spatial resolution, temporal resolution and accuracy to assess their safe usage. Among the array of techniques available, it is noteworthy that ground-based synthetic aperture radar (GB-SAR) has not yet been widely adopted for this purpose. Despite its remarkable equilibrium between the aforementioned attributes, its sensitivity to atmospheric disruptions, specific acquisition geometry, and the requisite for phase unwrapping collectively contribute to constraining its usage. Several processing strategies are developed in this thesis to capitalise on all the opportunities of GB-SAR systems, such as continuous, flexible and autonomous observation combined with high resolutions and accuracy. The first challenge that needs to be solved is to accurately localise and estimate the azimuth of the GB-SAR to improve the geocoding of the image in the subsequent step. A ray tracing algorithm and tomographic techniques are used to recover these external parameters of the sensors. The introduction of corner reflectors for validation purposes confirms a significant error reduction. However, for the subsequent geocoding, challenges persist in scenarios involving vertical structures due to foreshortening and layover, which notably compromise the geocoding quality of the observed points. These issues arise when multiple points at varying elevations are encapsulated within a singular resolution cell, posing difficulties in pinpointing the precise location of the scattering point responsible for signal return. To surmount these hurdles, a Bayesian approach grounded in intensity models is formulated, offering a tool to enhance the accuracy of the geocoding process. The validation is assessed on a dam in the black forest in Germany, characterised by a very specific structure. The second part of this thesis is focused on the feasibility of using GB-SAR systems for long-term geodetic monitoring of large structures. A first assessment is made by testing large temporal baselines between acquisitions for epoch-wise monitoring. Due to large displacements, the phase unwrapping can not recover all the information. An improvement is made by adapting the geometry of the signal processing with the principal component analysis. The main case study consists of several campaigns from different stations at Enguri Dam in Georgia. The consistency of the estimated displacement map is assessed by comparing it to a numerical model calibrated on the plumblines data. It exhibits a strong agreement between the two results and comforts the usage of GB-SAR for epoch-wise monitoring, as it can measure several thousand points on the dam. It also exhibits the possibility of detecting local anomalies in the numerical model. Finally, the instrument has been installed for continuous monitoring for over two years at Enguri Dam. An adequate flowchart is developed to eliminate the drift happening with classical interferometric algorithms to achieve the accuracy required for geodetic monitoring. The analysis of the obtained time series confirms a very plausible result with classical parametric models of dam deformations. Moreover, the results of this processing strategy are also confronted with the numerical model and demonstrate a high consistency. The final comforting result is the comparison of the GB-SAR time series with the output from four GNSS stations installed on the dam crest. The developed algorithms and methods increase the capabilities of the GB-SAR for dam monitoring in different configurations. It can be a valuable and precious supplement to other classical sensors for long-term geodetic observation purposes as well as short-term monitoring in cases of particular dam operations

Fortgeschrittene InSAR Methodologie zum Studium vom Bodensenkung und Rissbildung aufgrund von Grundwasserentnahmen im Tal von Mexiko

Radar remote sensing techniques are well suited for deformation studies. The Mexico City subsidence,for example, has been mapped using both the conventional and multi-temporal methods; however, no complete characterization and detailed temporal analysis of the land settlement in the entire Valley of Mexico, covering the lakebed of the five ancient lakes (Chalco, Xochimilco, Texcoco, Xaltocan and Zumpango) has been performed until now. In this work, we mapped and analysed the subsidence and associated earth fissuring in the Valley by exploiting, for the first time, the Small Baseline method from StaMPS. The inversion methodology was studied in detail and interpreted, and the algorithm was adjusted to select a spatial reference on the basis of the surface geology information. This extended algorithm was assessed by comparing the results obtained with existing ones particularly over the southern Valley. Furthermore, unwrapping and quality of the times series were analysed using maps of system misclosure. Our results indicate that the proposed algorithm adapts adequately to the study area. Detailed ERS and ENVISAT conventional and multi-temporal InSAR analysis for the 1999-2000 and 2002-2010 periods, respectively, were performed on northern Valley of Mexico. Both urban and rural areas are experiencing subsidence, and rapid rates were found in densely populated areas or where sizeable volumes of water are used for crop irrigation. Time series were used to evaluate the impact of the subsidence on important infrastructure such as the Tunel Emisor Oriente. As second main aspect, the flexibility of the proposed InSAR algorithm to identify points undergoing non-linear deformation was exploited to develop a methodology that contributes to the location of soil fractures and to the understanding of their dynamics. Fissure-prone zones identified by this method, effectively coincided with existing records of ground failures. The fracture trigger mechanisms are furthermore discussed and evaluated where notable acceleration or deceleration is found. The proposed soil fracture identification approach provided useful and valuable information for improving the vulnerability maps in the area.Radarfernerkundungstechniken sind gut geeignet um Deformationsprozesse zu studieren. Beispielsweise wurden die Setzungen in Mexico City mit konventionellen und multitemporalen Methoden erfasst; allerdings wurde bis jetzt keine komplette Charakterisierung und detaillierte zeitliche Analyse der Landbesiedelung im gesamten Tal von Mexiko, die das Seebett von fünf ehemaligen Seen (Chalco, Xochimilco, Texcoco, Xaltocan und Zumpango) beinhaltet, durchgeführt. In dieser Arbeit wurde die Bodensenkungen und die dazugehörigen Boden-Brüche im Tal von Mexiko mit Hilfe der Small Baseline Methode von StaMPS kartiert und analysiert. Die dazugehörige Inversionsmethode wurde im Detail studiert und interpretiert und dieser Algorithmus auf Basis der geologischen Information so angepasst, dass die Ergebnisse als räumliche Referenz dienen können. Dieser erweiterte Algorithmus wurde durch den Vergleich mit existierenden Ergebnissen aus dem südlichen Tal validiert. Das „Unwrapping“ und die Qualität der Zeitreihen wurden mit statistischen Verfahren bewertet. Detaillierte Analysen von ERS- und ENVISAT-Daten mit konventionellem und multitemporalem InSAR für die Zeiträume von 1999-2000 und von 2002-2010 wurden im Norden des Talbereiches von Mexico durchgeführt. Sowohl die städtischen als auch die ländlichen Bereiche erfahren Bodensenkungen. Große Setzungsraten wurden besonders in dicht bevölkerten Gebieten gefunden oder in Bereichen mit beträchtlicher Wasserentnahme zur Feldbewässerung. Die Zeitreihen wurden verwendet um die Auswirkungen der GW-Entnahme auf wichtige Infrastrukturprojekte zu bewerten,z.B. den Tunel Emisor Oriente. Als weiterer Schwerpunkt wurde die Flexibilität des verwendeten InSAR Algorithmus genutzt, um nichtlineare Verformung zu identifizieren und eine Methode zur Lokalisierung von Boden-Bruchzonen zu entwickeln und um ihre Dynamik zu verstehen. Die Lage der mit dieser Methode identifizierten Bruchzonen stimmt mit existierenden Aufzeichnungen von Bruchaktivitäten überein. Die Bruchauslösemechanismen werden an den Stellen diskutiert und bewertet, an denen deutliche Beschleunigungen oder Verzögerungen erkannt wurden. Der vorgestellte Ansatz zur Identifikation der Brüche stellt nützliche und wertvolle Informationen für die Verbesserung der Schadenskarten in diesem Gebiet dar

Generic interferometric synthetic aperture radar atmospheric correction model and its application to co- and post-seismic motions

PhD ThesisThe tremendous development of Interferometric Synthetic Aperture Radar (InSAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses more challenges for correcting atmospheric effects due to the spatial-temporal variability of atmospheric delays. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate the atmospheric delays, but they are limited by (i) the availability (and distribution) of GPS stations; (ii) the time difference between NWM and radar observations; and (iii) the difficulties in quantifying their performance. To overcome the abovementioned limitations, we have developed the Iterative Tropospheric Decomposition (ITD) model to reduce the coupling effects of the troposphere turbulence and stratification and hence achieve similar performances over flat and mountainous terrains. Highresolution European Centre for Medium-Range Weather Forecasts (ECMWF) and GPS-derived tropospheric delays were properly integrated by investigating the GPS network geometry and topography variations. These led to a generic atmospheric correction model with a range of notable features: (i) global coverage, (ii) all-weather, all-time usability, (iii) available with a maximum of two-day latency, and (iv) indicators available to assess the model’s performance and feasibility. The generic atmospheric correction model enables the investigation of the small magnitude coseismic deformation of the 2017 Mw-6.4 Nyingchi earthquake from InSAR observations in spite of substantial atmospheric contamination. It can also minimize the temporal correlations of InSAR atmospheric delays so that reliable velocity maps over large spatial extents can be achieved. Its application to the post-seismic motion following the 2016 Kaikoura earthquake shows a success to recover the time-dependent afterslip distribution, which in turn evidences the deep inactive subduction slip mechanism. This procedure can be used to map surface deformation in other scenarios including volcanic eruptions, tectonic rifting, cracking, and city subsidence.This work was supported by a Chinese Scholarship Council studentship. Part of this work was also supported by the UK NERC through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET)

Interferometric Synthetic Aperture Radar for slow slip applications

Over the last two decades, Slow Slip Events (SSEs) have been observed across many subduction zones, primarily through continuous GNSS networks. SSEs represent shearing of two tectonic plates, at much slower rates than earthquakes but more rapidly than plate motion. They are not dangerous in themselves, but change the stress field and can potentially trigger devastating earthquakes. While highly valuable, GNSS networks at most locations lack the spatial-resolution required to describe the spatial extent of the slow slip at depth. A better constraint of slow slip at depth in combination with other observations from seismology could be essential in addressing key research questions. These include: “Why do slow slip events occurs in some regions and not others?”, “What drives slow slip events?”, “Do slow slip events delay the occurrence of devastating earthquakes?”, and “Can slow slip events trigger devastating earthquakes?”. Interferometric Synthetic Aperture Radar (InSAR) is an established and attractive technique to study surface displacements at high-spatial resolution. Until now, InSAR has not been fully exploited for the study of SSEs. Here, I provide the necessary InSAR methodology, and further demonstrate the use of InSAR for static and time-dependant slow slip modelling. My developments have a direct benefit for various other applications such as earthquake cycle processes. I Specifically address the following two challenges which limit the wide uptake of InSAR: (1) Decorrelation noise introduced by changing backscattering properties of the surface and a change in satellite acquisition geometry, making it difficult to correctly unwrap meaningful signal. I address this problem by applying existing advanced time-series InSAR processing methods. (2) Atmospheric delays masking the smaller slow slip signal. These are mainly due to spatial and temporal variations in pressure, temperature, and relative humidity in the lower part of the troposphere, which result in an apparent signal in the InSAR data. Different tropospheric correction methods exist, all with their own limitations. Auxiliary data methods often lack the spatial and temporal resolution, while the phase-based methods cannot account for a spatially-varying troposphere. In response, I develop a phase-based power-law representation of tropospheric delay that can be applied in the presence of deformation and which accounts for spatial variation of tropospheric properties. I demonstrate its application over Mexico, where it reduces tropospheric signals both locally (on average by ~0.45 cm for each kilometer of elevation) and the long wavelength components. Moreover, I provide to the research community a Toolbox for Reducing Atmospheric InSAR Noise (TRAIN), which includes all the state-of-the-art correction methods, implemented as opensource matlab routines. When comparing these methods, I find spectrometers give the largest reduction in tropospheric noise, but are limited to cloud-free and daylight acquisitions. I also find that all correction methods perform ~10-20% worse when there is cloud cover. As all methods have their own limitations, future efforts should aim at combining the different correction methods in an optimal manner. Additionally, I apply my InSAR methodology and power-law correction method to the study of the 2006 Guerrero SSE, where I jointly invert cumulative GNSS and InSAR SSE surface displacements. In Guerrero, SSEs have been observed in a “seismic gap”, where no earthquakes have occurred since 1911, accumulating a seismic potential of Mw 8.0-8.4. I find slow slip enters the seismogenic zone and the Guerrero Gap, with ~5 cm slip reaching depths as shallow as 12 km, and where the spatial extent of the slow slip collocates on the interface with a highly coupled inter-SSE region as found from an GNSS study. In addition, slow slip decreased the total accumulated moment since the previous SSE (4.7 years earlier) by ~50% Over time and while accounting for SSEs, the moment deficit in the Guerrero Gap increases each year by Mw ~6.8. Therefore I find that the Guerrero Gap still has the potential for a large earthquake, with a seismic potential of Mw ~8.15 accumulated over the last century. Finally, I show the application to use InSAR for time-dependant slow slip modelling. From a simulation of the 2006 SSE, I demonstrate that InSAR is able to provide valuable information to constrain the spatial extent of the slow slip signal. With a future perspective of continued high repeat acquisitions of various SAR platforms, my expansion of the Network Inversion Filter with InSAR will become a powerful tool for investigating the spatio-temporal correlation between slow slip and other phenomena such as non volcanic tremor. Moreover, this approach can apply to earthquake cycle processes. Studying the broader earthquake cycle will further our knowledge of seismic hazard and increase our resilience to such events