Improved Goldstein Interferogram Filter Based on Local Fringe Frequency Estimation

The quality of an interferogram, which is limited by various phase noise, will greatly affect the further processes of InSAR, such as phase unwrapping. Interferometric SAR (InSAR) geophysical measurements’, such as height or displacement, phase filtering is therefore an essential step. In this work, an improved Goldstein interferogram filter is proposed to suppress the phase noise while preserving the fringe edges. First, the proposed adaptive filter step, performed before frequency estimation, is employed to improve the estimation accuracy. Subsequently, to preserve the fringe characteristics, the estimated fringe frequency in each fixed filtering patch is removed from the original noisy phase. Then, the residual phase is smoothed based on the modified Goldstein filter with its parameter alpha dependent on both the coherence map and the residual phase frequency. Finally, the filtered residual phase and the removed fringe frequency are combined to generate the filtered interferogram, with the loss of signal minimized while reducing the noise level. The effectiveness of the proposed method is verified by experimental results based on both simulated and real data

An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation

Phase filtering and pixel quality (coherence) estimation is critical in producing Digital Elevation Models (DEMs) from Interferometric Synthetic Aperture Radar (InSAR) images, as it removes spatial inconsistencies (residues) and immensely improves the subsequent unwrapping. Large amount of InSAR data facilitates Wide Area Monitoring (WAM) over geographical regions. Advances in parallel computing have accelerated Convolutional Neural Networks (CNNs), giving them advantages over human performance on visual pattern recognition, which makes CNNs a good choice for WAM. Nevertheless, this research is largely unexplored. We thus propose "GenInSAR", a CNN-based generative model for joint phase filtering and coherence estimation, that directly learns the InSAR data distribution. GenInSAR's unsupervised training on satellite and simulated noisy InSAR images outperforms other five related methods in total residue reduction (over 16.5% better on average) with less over-smoothing/artefacts around branch cuts. GenInSAR's Phase, and Coherence Root-Mean-Squared-Error and Phase Cosine Error have average improvements of 0.54, 0.07, and 0.05 respectively compared to the related methods.Comment: to be published in a future issue of IEEE Geoscience and Remote Sensing Letter

Identification of Sea Level Rise and Land Subsidence Based on Sentinel 1 Data in the Coastal City of Pekalongan, Central Java, Indonesia

Sea level rise is a pure impact of climate change. However, the process of studying sea level rise must include local factors that influence such as land subsidence. This study focuses on sea level rise using the CEEMDAN method and land subsidence using the DInSAR method. The location of this research is Pekalongan, Central Java, Indonesia. Tidal data used in this study was for five years, from 2016 to 2020, obtained from the Geospatial Information Agency (BIG). Then the data used to study land subsidence in this study uses Sentinel-1 Synthetic Aperture Radar (SAR) data in 2015, 2016, 2017, and 2020. Pekalongan is an area with mixed diurnal tidal types with Formzahl number 1.7. The sea level rise in Pekalongan is relatively high, at 10.6 mm/year. Then the land subsidence that occurred in Pekalongan is the phenomenon that has the most influence on the occurrence of coastal flooding in the region. The average land subsidence on the coast of Pekalongan is 5.37 cm/year. In addition, the sampling results in 6 areas showed that the most significant decrease was in Area 2, with a decrease of -7.91 cm/year. Based on this research, land subsidence is the most considerable influence on flooding in Pekalongan compared to sea level rise

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)

Monitoring von Hangbewegungen mit InSAR Techniken im Gebiet Ciloto, Indonesien

In this doctoral thesis, the InSAR techniques are applied to detect the ground movement phenomenon and to assess the InSAR result geometrically in the Ciloto area, Indonesia. Mainly, one of those techniques, the SB-SDFP algorithm, overcomes the limitations of conventional InSAR in monitoring rural and agricultural areas and can observe extremely slow landslides. The InSAR strategy is positively known as a promising option to detect and quantify the kinematics of active landslides on a large areal scale. To minimize the bias of the InSAR displacement result, the correction of the tropospheric phase delay was carried out in a first step. This procedure is demonstrated in experiments both in the small study area in Ciloto and in a larger area. The latter is an area located in Northern Baja California, Mexico and is dominated by tectonic activity as well as groundwater-induced subsidence. A detailed investigation of the slope movement's behavior in the Ciloto district was conducted utilizing multi-temporal and multi-band SAR data from ERS1/2 (1996-1999), ALOS PALSAR (2007-2009) and Sentinel-1 (2014-2018) satellites. The region was successfully identified as a permanent active landslide prone area, especially in the vicinity of the Puncak Pass and Puncak Highway. The full 3D velocity field and the displacement time series were estimated using the inversion model. The velocity rate was classified from extremely slow to slow movement. To comprehend the landslide's behavior, a further examination of the relationship between InSAR results and physical characteristics of the area was carried out. For the long period of a slow-moving landslide, the relationship between precipitation and displacement trend shows a weak correlation. It is concluded that the extremely slow to slow deformation is not directly influenced by the rainfall intensity, yet it effectuates the subsurface and the groundwater flow. The run-off process with rainfall exceeding a soil's infiltration capacity was suspected as the main driver of the slow ground movement phenomenon. However, when analyzing rapid and extremely rapid landslide events at Puncak Pass, a significant increase in the correlation coefficient between precipitation and displacement rate could be observed.In dieser Doktorarbeit wird die Anwendung von erweiterten Verarbeitungsstrategien von InSAR Daten zur Erkennung und geometrischen Bewertung der Bodenbewegungen im Ciloto - Indonesien dargestellt. Dieser Ansatz überwindet die Beschränkungen konventioneller SAR-Interferometrie und ermöglicht sowohl ein kontinuierliches Monitoring dieses landwirtschaftich geprägten Gebietes als auch die Erfassung extrem langsamer Hangrutschungen. Um eine Verzerrung der InSAR Deformationsergebnisse zu minimieren, wurde zunächst eine Korrektur der troposphärischen Phase durchgeführt. Diese neuartige Strategie wird sowohl im Forschungsgebiet Ciloto als auch an einem größeren Gebiet demonstriert. Bei letzterem handelt es sich um einen Küstenstreifen im nördlichen Niederkalifornien, Mexiko, welcher durch hohe tektonische Aktivität und grundwasserinduzierte Landsetzungen charakterisiert ist. Die detaillierte Untersuchung des Verhaltens von Hangrutschungen im Ciloto erfolgte durch die Verarbeitung multi-temporaler SAR-Daten unter Nutzung verschiedener Frequenzbänder, darunter ESR1/2 (1996-1999), ALOS PALSAR (2007-2009) und Sentinel-1 (2014-2018) Daten. Die Region konnte erfolgreich als permanent aktives Hangrutschungsgebiet identifiziert werden, wobei der Puncak Pass und der Puncak Highway ein erhöhtes Gefahrenpotential aufweisen. Ein 3D- Geschwindig-keitsfeld der Deformation und die zugehörigen Zeitreihen wurden mit dem Inversionsmodell berechnet. Die Geschwindigkeitsrate wurde als langsam bis extrem langsam klassifiziert. Um das dynamische Verhalten der Hangrutschung zu verstehen wurde, in einer weiteren Untersuchung die Beziehung zwischen dem InSAR-Ergebnis und den physikalischen Begebenheiten im Forschungsgebiet analysiert. Es wird der Schluss gezogen, dass die langsame bis extrem langsame Verformung nicht direkt von der Niederschlagsintensität beeinflusst wird, diese sich aber auf den Untergrund und die Grundwasserströmung auswirkt. Es wird vermutet, dass der Oberflächenablauf, welcher die Infiltrationskapazität des Bodens übersteigt, ausschlaggebend für das Phänomen der langsamen Bodenbewegung ist. Für die schnellen und extrem schnellen Hangrutschungen jedoch konnte eine signifikante Erhöhung des Korrelationskoeffizienten zwischen Niederschlag und Verschiebungsrate bei Untersuchungen der Hangrutschung am Puncak-Pass nachgewiesen werden

Orbital Effects in Spaceborne Synthetic Aperture Radar Interferometry

This book reviews and investigates orbit-related effects in synthetic aperture Radar interferometry (InSAR). The translation of orbit inaccuracies to error signals in the interferometric phase is concisely described; estimation and correction approaches are discussed and evaluated with special focus on network adjustment of redundantly estimated baseline errors. Moreover, the effect of relative motion of the orbit reference frame is addressed

Non-local methods for InSAR parameters estimation

In the thesis work the nonlocal paradigm has been investigated in the framework of Multitemporal SAR Interferometry, e.g. Differential Interferometry, Tomography, etc., and single InSAR pair, e.g. DEM generation. In the former, Adaptive Multi-Looking methods have been developed for the generation of interferometric data-stacks. Following the nonlocal approach, the proposed methods rely only on similar pixels according to a suitable similarity measure that exploits the stack's temporal information. An hybrid approach that jointly uses the nonlocal paradigm and transform domain filtering has been investigated for InSAR pair phase estimation. On the track of the BM3D and SARBM3D algorithms, different approaches to the filtering in the transform domain are investigated. Furthermore, a novel approach to the similarity computation and filtering, based on a relative-topography content of the interferometric phase rather than its absolute value, is proposed

Surface deformation analysis in Northeast Italy by using PS-InSAR and GNSS data

In the present study, we exploited the potential of satellite-based geodetic data for detecting and measuring surface displacement in Northeast Italy. In this contest, we focused mainly on 1) the estimation of the interseismic deformation during the satellites’ observation period, 2) the detection and analysis of the main deformation patterns, and 3) the correlation of the signals to the active tectonic structures. Despite the low convergence rates (~ 1.5-3 mm/yr), Northeast Italy is an active tectonic area, as testified by the instrumental and historical seismicity. The Adria-Eurasia convergence is mainly accommodated by the thrusts and strike-slip faults of the Southeastern Alps and the External Dinarides, located in the northern and northeastern sectors of the study area. The Venetian-Friulian plain and the Adriatic coasts, affected by active subsidence, dominate the southern region. We used the Stanford Method for Persistent Scatterers (StaMPS) applied to Sentinel-1 SAR images acquired along the ascending and descending orbit tracks between 2015 and 2019. Based on a stack of single-master differential interferograms, we detected coherent and temporally stable pixels based on amplitude and phase noise analysis. After applying spatial-temporal filters and additional post-processing operations to refine the measurements, we used Adria-fixed GNSS velocities derived by permanent stations in the study area to calibrate the InSAR velocities. The outcome consists of Line-OF-Sight (LOS) mean ground velocity maps derived by displacement time series along the radar directions for each satellite track. The combination of the LOS datasets yields vertical and east-west velocity maps, which are mostly in agreement with GNSS data and previous geodetic studies. Based on our measurements, we observe a significant positive velocity gradient of 1 mm/yr across the westernmost sector of the Alpine system, suggesting an aseismic motion of the root of the Bassano-Valdobbiadene thrust. The positive vertical gradients (~1 and up to 2 mm/yr) across the Alpine-Dinaric systems in the central and eastern sectors and the eastward motion that increases northeastward (1-2 mm/yr) may be related to the active Alpine-Dinaric thrusts and strike-slip faults. We also suggest that the detected westward motion of the Friulian plain (around Udine) might be attributed to the presence of tectonic structures characterized by transcurrent-transpressive kinematics. Finally, we detect other signals, such as the significant subsidence (2-4 mm/yr) along the coasts and on the southern Venetian-Friulian plain, confirming the correlation between subsidence and the geological setting of the study area. In conclusion, our study confirms the potential of MT-InSAR and GNSS data for the estimation of the surface deformations in response to active tectonics, even in areas characterized by low deformation rates, such as Northeast Italy.In the present study, we exploited the potential of satellite-based geodetic data for detecting and measuring surface displacement in Northeast Italy. In this contest, we focused mainly on 1) the estimation of the interseismic deformation during the satellites’ observation period, 2) the detection and analysis of the main deformation patterns, and 3) the correlation of the signals to the active tectonic structures. Despite the low convergence rates (~ 1.5-3 mm/yr), Northeast Italy is an active tectonic area, as testified by the instrumental and historical seismicity. The Adria-Eurasia convergence is mainly accommodated by the thrusts and strike-slip faults of the Southeastern Alps and the External Dinarides, located in the northern and northeastern sectors of the study area. The Venetian-Friulian plain and the Adriatic coasts, affected by active subsidence, dominate the southern region. We used the Stanford Method for Persistent Scatterers (StaMPS) applied to Sentinel-1 SAR images acquired along the ascending and descending orbit tracks between 2015 and 2019. Based on a stack of single-master differential interferograms, we detected coherent and temporally stable pixels based on amplitude and phase noise analysis. After applying spatial-temporal filters and additional post-processing operations to refine the measurements, we used Adria-fixed GNSS velocities derived by permanent stations in the study area to calibrate the InSAR velocities. The outcome consists of Line-OF-Sight (LOS) mean ground velocity maps derived by displacement time series along the radar directions for each satellite track. The combination of the LOS datasets yields vertical and east-west velocity maps, which are mostly in agreement with GNSS data and previous geodetic studies. Based on our measurements, we observe a significant positive velocity gradient of 1 mm/yr across the westernmost sector of the Alpine system, suggesting an aseismic motion of the root of the Bassano-Valdobbiadene thrust. The positive vertical gradients (~1 and up to 2 mm/yr) across the Alpine-Dinaric systems in the central and eastern sectors and the eastward motion that increases northeastward (1-2 mm/yr) may be related to the active Alpine-Dinaric thrusts and strike-slip faults. We also suggest that the detected westward motion of the Friulian plain (around Udine) might be attributed to the presence of tectonic structures characterized by transcurrent-transpressive kinematics. Finally, we detect other signals, such as the significant subsidence (2-4 mm/yr) along the coasts and on the southern Venetian-Friulian plain, confirming the correlation between subsidence and the geological setting of the study area. In conclusion, our study confirms the potential of MT-InSAR and GNSS data for the estimation of the surface deformations in response to active tectonics, even in areas characterized by low deformation rates, such as Northeast Italy