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This thesis presents new approaches of SAR methods and their application to tectonically active systems and related surface deformation. With 3 publications two case studies are presented:
(1) The coseismic deformation related to the Nura earthquake (5th October 2008, magnitude Mw 6.6) at the eastern termination of the intramontane Alai valley. Located between the southern Tien Shan and the northern Pamir the coseismic surface displacements are analysed using SAR (Synthetic Aperture RADAR) data. The results show clear gradients in the vertical and horizontal directions along a complex pattern of surface ruptures and active faults. To integrate and to interpret these observations in the context of the regional active tectonics a SAR data analysis is complemented with seismological data and geological field observations. The main moment release of the Nura earthquake appears to be on the Pamir Frontal thrust, while the main surface displacements and surface rupture occurred in the footwall and along of the NE–SW striking Irkeshtam fault. With InSAR data from ascending and descending satellite tracks along with pixel offset measurements the Nura earthquake source is modelled as a segmented rupture. One fault segment corresponds to high-angle brittle faulting at the Pamir Frontal thrust and two more fault segments show moderate-angle and low-friction thrusting at the Irkeshtam fault. The integrated analysis of the coseismic deformation argues for a rupture segmentation and strain partitioning associated to the earthquake. It possibly activated an orogenic wedge in the easternmost segment of the Pamir-Alai collision zone. Further, the style of the segmentation may be associated with the presence of Paleogene evaporites.
(2) The second focus is put on slope instabilities and consequent landslides in the area of prominent topographic transition between the Fergana basin and high-relief Alai range. The Alai range constitutes an active orogenic wedge of the Pamir – Tien Shan collision zone that described as a progressively northward propagating fold-and-thrust belt. The interferometric analysis of ALOS/PALSAR radar data integrates a period of 4 years (2007-2010) based on the Small Baseline Subset (SBAS) time-series technique to assess surface deformation with millimeter surface change accuracy. 118 interferograms are analyzed to observe spatially-continuous movements with downslope velocities up to 71 mm/yr. The obtained rates indicate slow movement of the deep-seated landslides during the observation time. We correlated these movements with precipitation and seismic records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with one earthquake event. In the next step, to understand the spatial pattern of landslide processes, the tectonic morphologic and lithologic settings are combined with the patterns of surface deformation. We demonstrate that the lithological and tectonic structural patterns are the main controlling factors for landslide occurrence and surface deformation magnitudes. Furthermore active contractional deformation in the front of the orogenic wedge is the main mechanism to sustain relief. Some of the slower but continuously moving slope instabilities are directly related to tectonically active faults and unconsolidated young Quaternary syn-orogenic sedimentary sequences. The InSAR observed slow moving landslides represent active deep-seated gravitational slope deformation phenomena which is first time observed in the Tien Shan mountains. Our approach offers a new combination of InSAR techniques and tectonic aspects to localize and understand enhanced slope instabilities in tectonically active mountain fronts in the Kyrgyz Tien Shan.
Crustal deformation can be the result of volcanic and tectonic activity such as fault dislocation and magma intrusion. The crustal deformation may precede and/or succeed the earthquake occurrence and eruption. Mitigating the associated hazard, continuous monitoring of the crustal deformation accordingly has become an important task for geo-observatories and fast response systems. Due to highly non-linear behavior of the crustal deformation fields in time and space, which are not always measurable using conventional geodetic methods (e.g., Leveling), innovative techniques of monitoring and analysis are required. In this thesis I describe novel methods to improve the ability for precise and accurate mapping the spatiotemporal surface deformation field using multi acquisitions of satellite radar data. Furthermore, to better understand the source of such spatiotemporal deformation fields, I present novel static and time dependent model inversion approaches. Almost any interferograms include areas where the signal decorrelates and is distorted by atmospheric delay. In this thesis I detail new analysis methods to reduce the limitations of conventional InSAR, by combining the benefits of advanced InSAR methods such as the permanent scatterer InSAR (PSI) and the small baseline subsets (SBAS) with a wavelet based data filtering scheme. This novel InSAR time series methodology is applied, for instance, to monitor the non-linear deformation processes at Hawaii Island. The radar phase change at Hawaii is found to be due to intrusions, eruptions, earthquakes and flank movement processes and superimposed by significant environmental artifacts (e.g., atmospheric). The deformation field, I obtained using the new InSAR analysis method, is in good agreement with continuous GPS data. This provides an accurate spatiotemporal deformation field at Hawaii, which allows time dependent source modeling. Conventional source modeling methods usually deal with static deformation field, while retrieving the dynamics of the source requires more sophisticated time dependent optimization approaches. This problem I address by combining Monte Carlo based optimization approaches with a Kalman Filter, which provides the model parameters of the deformation source consistent in time. I found there are numerous deformation sources at Hawaii Island which are spatiotemporally interacting, such as volcano inflation is associated to changes in the rifting behavior, and temporally linked to silent earthquakes. I applied these new methods to other tectonic and volcanic terrains, most of which revealing the importance of associated or coupled deformation sources. The findings are 1) the relation between deep and shallow hydrothermal and magmatic sources underneath the Campi Flegrei volcano, 2) gravity-driven deformation at Damavand volcano, 3) fault interaction associated with the 2010 Haiti earthquake, 4) independent block wise flank motion at the Hilina Fault system, Kilauea, and 5) interaction between salt diapir and the 2005 Qeshm earthquake in southern Iran. This thesis, written in cumulative form including 9 manuscripts published or under review in peer reviewed journals, improves the techniques for InSAR time series analysis and source modeling and shows the mutual dependence between adjacent deformation sources. These findings allow more realistic estimation of the hazard associated with complex volcanic and tectonic systems.
Large-scale volcanic deformation recently detected by radar interferometry (InSAR) provides new information and thus new scientific challenges for understanding volcano-tectonic activity and magmatic systems. The destabilization of such a system at depth noticeably affects the surrounding environment through magma injection, ground displacement and volcanic eruptions. To determine the spatiotemporal evolution of the Lazufre volcanic area located in the central Andes, we combined short-term ground displacement acquired by InSAR with long-term geological observations. Ground displacement was first detected using InSAR in 1997. By 2008, this displacement affected 1800 km2 of the surface, an area comparable in size to the deformation observed at caldera systems. The original displacement was followed in 2000 by a second, small-scale, neighbouring deformation located on the Lastarria volcano. We performed a detailed analysis of the volcanic structures at Lazufre and found relationships with the volcano deformations observed with InSAR. We infer that these observations are both likely to be the surface expression of a long-lived magmatic system evolving at depth. It is not yet clear whether Lazufre may trigger larger unrest or volcanic eruptions; however, the second deformation detected at Lastarria and the clear increase of the large-scale deformation rate make this an area of particular interest for closer continuous monitoring.
Megathrust earthquakes impose changes of differential stress and pore pressure in the lithosphere-asthenosphere system that are transiently relaxed during the postseismic period primarily due to afterslip, viscoelastic and poroelastic processes.
Especially during the early postseismic phase, however, the relative contribution of these processes to the observed surface deformation is unclear.
To investigate this, we use geodetic data collected in the first 48 days following the 2010 Maule earthquake and a poro-viscoelastic forward model combined with an afterslip inversion.
This model approach fits the geodetic data 14% better than a pure elastic model. Particularly near the region of maximum coseismic slip, the predicted surface poroelastic uplift pattern explains well the observations.
If poroelasticity is neglected, the spatial afterslip distribution is locally altered by up to +/- 40%.
Moreover, we find that shallow crustal aftershocks mostly occur in regions of increased postseismic pore-pressure changes, indicating that both processes might be mechanically coupled.
Landslides are one of the biggest natural hazards in Georgia, a mountainous country in the Caucasus. So far, no systematic monitoring and analysis of the dynamics of landslides in Georgia has been made. Especially as landslides are triggered by extrinsic processes, the analysis of landslides together with precipitation and earthquakes is challenging. In this thesis I describe the advantages and limits of remote sensing to detect and better understand the nature of landslide in Georgia. The thesis is written in a cumulative form, composing a general introduction, three manuscripts and a summary and outlook chapter. In the present work, I measure the surface displacement due to active landslides with different interferometric synthetic aperture radar (InSAR) methods. The slow landslides (several cm per year) are well detectable with two-pass interferometry. In same time, the extremely slow landslides (several mm per year) could be detected only with time series InSAR techniques. I exemplify the success of InSAR techniques by showing hitherto unknown landslides, located in the central part of Georgia. Both, the landslide extent and displacement rate is quantified. Further, to determine a possible depth and position of potential sliding planes, inverse models were developed. Inverse modeling searches for parameters of source which can create observed displacement distribution. I also empirically estimate the volume of the investigated landslide using displacement distributions as derived from InSAR combined with morphology from an aerial photography. I adapted a volume formula for our case, and also combined available seismicity and precipitation data to analyze potential triggering factors. A governing question was: What causes landslide acceleration as observed in the InSAR data? The investigated area (central Georgia) is seismically highly active. As an additional product of the InSAR data analysis, a deformation area associated with the 7th September Mw=6.0 earthquake was found. Evidences of surface ruptures directly associated with the earthquake could not be found in the field, however, during and after the earthquake new landslides were observed. The thesis highlights that deformation from InSAR may help to map area prone landslides triggering by earthquake, potentially providing a technique that is of relevance for country wide landslide monitoring, especially as new satellite sensors will emerge in the coming years.
This study demonstrates the potential of using single-pass TanDEM-X (TDX) radar imagery to analyse inter- and intra-annual glacier changes in mountainous terrain. Based on SAR images acquired in February 2012, March 2013 and November 2013 over the Inylchek Glacier, Kyrgyzstan, we discuss in detail the processing steps required to generate three reliable digital elevation models (DEMs) with a spatial resolution of 10 m that can be used for glacial mass balance studies. We describe the interferometric processing steps and the influence of a priori elevation information that is required to model long wavelength topographic effects. We also focus on DEM alignment to allow optimal DEM comparisons and on the effects of radar signal penetration on ice and snow surface elevations. We finally compare glacier elevation changes between the three TDX DEMs and the C-band shuttle radar topography mission (SRTM) DEM from February 2000. We introduce a new approach for glacier elevation change calculations that depends on the elevation and slope of the terrain. We highlight the superior quality of the TDX DEMs compared to the SRTM DEM, describe remaining DEM uncertainties and discuss the limitations that arise due to the side-looking nature of the radar sensor. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
LiCSBAS
(2020)
For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.
LiCSBAS
(2020)
For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (similar to km) relative displacements with an accuracy of <1 cm/epoch and similar to 2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.
Alfred Wegeners ideas on continental drift were doubted for several decades until the discovery of polarization changes at the Atlantic seafloor and the seismic catalogs imaging oceanic subduction underneath the continental crust (Wadati-Benioff Zone). It took another 20 years until plate motion could be directly observed and quantified by using space geodesy. Since then, it is unthinkable to do neotectonic research without the use of satellite-based methods.
Thanks to a tremendeous increase of instrumental observations in space and time over the last decades we significantly increased our knowledge on the complexity of the seismic cycle, that is, the interplay of tectonic stress build up and release. Our classical assumption, earthquakes were the only significant phenomena of strain release previously accumulated in a linear fashion, is outdated. We now know that this concept is actually decorated with a wide range of slow and fast processes such as triggered slip, afterslip, post-seismic and visco-elastic relaxation of the lower crust, dynamic pore-pressure changes in the elastic crust, aseismic creep, slow slip events and seismic swarms. On the basis of eleven peer-reviewed papers studies I here present the diversity of crustal deformation processes. Based on time-series analyses of radar imagery and satellited-based positioning data I quantify tectonic surface deformation and use numerical and analytical models and independent geologic and seismologic data to better understand the underlying crustal processes.
The main part of my work focuses on the deformation observed in the Pamir, the Hindu Kush and the Tian Shan that together build the highly active continental collision zone between Northwest-India and Eurasia. Centered around the Sarez earthquake that ruptured the center of the Pamir in 2015 I present diverse examples of crustal deformation phenomena. Driver of the deformation is the Indian indenter, bulldozing into the Pamir, compressing the orogen that then collapses westward into the Tajik depression. A second natural observatory of mine to study tectonic deformation is the oceanic subduction zone in Chile that repeatedly hosts large earthquakes of magnitude 8 and more. These are best to study post-seismic relaxation processes and coupling of large earthquake.
My findings nicely illustrate how complex fashion and how much the different deformation phenomena are coupled in space and time. My publications contribute to the awareness that the classical concept of the seismic cycle needs to be revised, which, in turn, has a large influence in the classical, probabilistic seismic hazard assessment that primarily relies on statistically solid recurrence times.
With the advent of the two Sentinel-1 (S1) satellites, Synthetic Aperture Radar (SAR) data with high temporal and spatial resolution are freely available. This provides a promising framework to facilitate detailed investigations of surface instabilities and movements on large scales with high temporal resolution, but also poses substantial processing challenges because of storage and computation requirements. Methods are needed to efficiently detect short term changes in dynamic environments. Approaches considering pair-wise processing of a series of consecutive scenes to retain maximum temporal resolution in conjunction with time series analyses are required. Here we present OSARIS, the “Open Source SAR Investigation System,” as a framework to process large stacks of S1 data on high-performance computing clusters. Based on Generic Mapping Tools SAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexible processing schemes, convenient configuration, and generation of geocoded stacks of analysis-ready base data, including amplitude, phase, coherence, and unwrapped interferograms. Time series analyses can be conducted by applying automated modules to the data stacks. The capabilities of OSARIS are demonstrated in a case study from the northwestern Tien Shan, Central Asia. After merging of slices, a total of 80 scene pairs were processed from 174 total input scenes. The coherence time series exhibits pronounced seasonal variability, with relatively high coherence values prevailing during the summer months in the nival zone. As an example of a time series analysis module, we present OSARIS' “Unstable Coherence Metric” which identifies pixels affected by significant drops from high to low coherence values. Measurements of motion provided by LOSD measurements require careful evaluation because interferometric phase unwrapping is prone to errors. Here, OSARIS provides a series of modules to detect and mask unwrapping errors, correct for atmospheric disturbances, and remove large-scale trends. Wall clock processing time for the case study (area ~9,000 km2) was ~12 h 4 min on a machine with 400 cores and 2 TB RAM. In total, ~12 d 10 h 44 min (~96%) were saved through parallelization. A comparison of selected OSARIS datasets to results from two state-of-the-art SAR processing suites, ISCE and SNAP, shows that OSARIS provides products of competitive quality despite its high level of automatization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years.