Deep Learning for InSAR Phase Filtering: An Optimized Framework for Phase Unwrapping

Interferometric Synthetic Aperture Radar (InSAR) data processing applications, such as deformation monitoring and topographic mapping, require an interferometric phase filtering step. Indeed, the filtering quality significantly impacts the deformation and terrain height estimation accuracy. However, the existing classical and deep learning-based phase filtering methods provide artefacts in the filtered areas where a large amount of noise prevents retrieving the original signal. In this way, we can no longer distinguish the underlying informative signal for the next processing step. This paper proposes a deep convolutional neural network filtering method, developing a novel learning strategy to preserve the initial phase noise input into these crucial areas. Thanks to the encoder–decoder powerful phase feature extraction ability, the network can predict an accurate coherence and filtered interferometric phase, ensuring reliable final results. Furthermore, we also address a novel Synthetic Aperture Radar (SAR) interferograms simulation strategy that, using initial parameters estimated from real SAR images, considers physical behaviors typical of a real acquisition. According to the results achieved on simulated and real InSAR data, the proposed filtering method significantly outperforms the classical and deep learning-based ones

Robust and Flexible Persistent Scatterer Interferometry for Long-Term and Large-Scale Displacement Monitoring

Die Persistent Scatterer Interferometrie (PSI) ist eine Methode zur Überwachung von Verschiebungen der Erdoberfläche aus dem Weltraum. Sie basiert auf der Identifizierung und Analyse von stabilen Punktstreuern (sog. Persistent Scatterer, PS) durch die Anwendung von Ansätzen der Zeitreihenanalyse auf Stapel von SAR-Interferogrammen. PS Punkte dominieren die Rückstreuung der Auflösungszellen, in denen sie sich befinden, und werden durch geringfügige Dekorrelation charakterisiert. Verschiebungen solcher PS Punkte können mit einer potenziellen Submillimetergenauigkeit überwacht werden, wenn Störquellen effektiv minimiert werden. Im Laufe der Zeit hat sich die PSI in bestimmten Anwendungen zu einer operationellen Technologie entwickelt. Es gibt jedoch immer noch herausfordernde Anwendungen für die Methode. Physische Veränderungen der Landoberfläche und Änderungen in der Aufnahmegeometrie können dazu führen, dass PS Punkte im Laufe der Zeit erscheinen oder verschwinden. Die Anzahl der kontinuierlich kohärenten PS Punkte nimmt mit zunehmender Länge der Zeitreihen ab, während die Anzahl der TPS Punkte zunimmt, die nur während eines oder mehrerer getrennter Segmente der analysierten Zeitreihe kohärent sind. Daher ist es wünschenswert, die Analyse solcher TPS Punkte in die PSI zu integrieren, um ein flexibles PSI-System zu entwickeln, das in der Lage ist mit dynamischen Veränderungen der Landoberfläche umzugehen und somit ein kontinuierliches Verschiebungsmonitoring ermöglicht. Eine weitere Herausforderung der PSI besteht darin, großflächiges Monitoring in Regionen mit komplexen atmosphärischen Bedingungen durchzuführen. Letztere führen zu hoher Unsicherheit in den Verschiebungszeitreihen bei großen Abständen zur räumlichen Referenz. Diese Arbeit befasst sich mit Modifikationen und Erweiterungen, die auf der Grund lage eines bestehenden PSI-Algorithmus realisiert wurden, um einen robusten und flexiblen PSI-Ansatz zu entwickeln, der mit den oben genannten Herausforderungen umgehen kann. Als erster Hauptbeitrag wird eine Methode präsentiert, die TPS Punkte vollständig in die PSI integriert. In Evaluierungsstudien mit echten SAR Daten wird gezeigt, dass die Integration von TPS Punkten tatsächlich die Bewältigung dynamischer Veränderungen der Landoberfläche ermöglicht und mit zunehmender Zeitreihenlänge zunehmende Relevanz für PSI-basierte Beobachtungsnetzwerke hat. Der zweite Hauptbeitrag ist die Vorstellung einer Methode zur kovarianzbasierten Referenzintegration in großflächige PSI-Anwendungen zur Schätzung von räumlich korreliertem Rauschen. Die Methode basiert auf der Abtastung des Rauschens an Referenzpixeln mit bekannten Verschiebungszeitreihen und anschließender Interpolation auf die restlichen PS Pixel unter Berücksichtigung der räumlichen Statistik des Rauschens. Es wird in einer Simulationsstudie sowie einer Studie mit realen Daten gezeigt, dass die Methode überlegene Leistung im Vergleich zu alternativen Methoden zur Reduktion von räumlich korreliertem Rauschen in Interferogrammen mittels Referenzintegration zeigt. Die entwickelte PSI-Methode wird schließlich zur Untersuchung von Landsenkung im Vietnamesischen Teil des Mekong Deltas eingesetzt, das seit einigen Jahrzehnten von Landsenkung und verschiedenen anderen Umweltproblemen betroffen ist. Die geschätzten Landsenkungsraten zeigen eine hohe Variabilität auf kurzen sowie großen räumlichen Skalen. Die höchsten Senkungsraten von bis zu 6 cm pro Jahr treten hauptsächlich in städtischen Gebieten auf. Es kann gezeigt werden, dass der größte Teil der Landsenkung ihren Ursprung im oberflächennahen Untergrund hat. Die präsentierte Methode zur Reduzierung von räumlich korreliertem Rauschen verbessert die Ergebnisse signifikant, wenn eine angemessene räumliche Verteilung von Referenzgebieten verfügbar ist. In diesem Fall wird das Rauschen effektiv reduziert und unabhängige Ergebnisse von zwei Interferogrammstapeln, die aus unterschiedlichen Orbits aufgenommen wurden, zeigen große Übereinstimmung. Die Integration von TPS Punkten führt für die analysierte Zeitreihe von sechs Jahren zu einer deutlich größeren Anzahl an identifizierten TPS als PS Punkten im gesamten Untersuchungsgebiet und verbessert damit das Beobachtungsnetzwerk erheblich. Ein spezieller Anwendungsfall der TPS Integration wird vorgestellt, der auf der Clusterung von TPS Punkten basiert, die innerhalb der analysierten Zeitreihe erschienen, um neue Konstruktionen systematisch zu identifizieren und ihre anfängliche Bewegungszeitreihen zu analysieren

Transient displacement analysis using double-pulsed ESPI and fringe processing methods

This thesis deals with techniques for the displacement measurement of fast transient phenomena using ESPI. Four main contributions are presented. First, a computer model for speckle noise and ESPI fringe generation is proposed. An assessment methodology for speckle noise reduction algorithms is then derived using the computer model. Then the noise in the ESPI fringe patterns is analysed using computer generated speckle and several solutions for its reduction are proposed and assessed. Finally, a fast electro-optical system is presented as a solution to the unambiguous phase extraction problem from a single interferogram. With this novel system, whole field transient displacements occurring in time intervals as short as 20ns can be successfully registered and retrieved. [Continues.

Ricerche di Geomatica 2011

Questo volume raccoglie gli articoli che hanno partecipato al Premio AUTeC 2011. Il premio è stato istituito nel 2005. Viene conferito ogni anno ad una tesi di Dottorato giudicata particolarmente significativa sui temi di pertinenza del SSD ICAR/06 (Topografia e Cartografia) nei diversi Dottorati attivi in Italia

InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances

Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique able to measure deformation of the earth’s surface over large areas. InSAR deformation analysis uses two main categories of backscatter: Persistent Scatterers (PS) and Distributed Scatterers (DS). While PS are characterized by a high signal-to-noise ratio and predominantly occur as single pixels, DS possess a medium or low signal-to-noise ratio and can only be exploited if they form homogeneous groups of pixels that are large enough to allow for statistical analysis. Although DS have been used by InSAR since its beginnings for different purposes, new methods developed during the last decade have advanced the field significantly. Preprocessing of DS with spatio-temporal filtering allows today the use of DS in PS algorithms as if they were PS, thereby enlarging spatial coverage and stabilizing algorithms. This review explores the relations between different lines of research and discusses open questions regarding DS preprocessing for deformation analysis. The review is complemented with an experiment that demonstrates that significantly improved results can be achieved for preprocessed DS during parameter estimation if their statistical properties are used

Towards an Integrated Assessment of Sea-Level Observations Along the U.S. Atlantic Coast

Sea levels are rising globally due to anthropogenic climate change. However, local sea levels that impact coastal ecosystems often differ from the global trend, sometimes by a factor of two or more. Improved understanding of this regional variability provides insights into geophysical processes and has implications for coastal communities developing resilience to ongoing sea-level rise. This dissertation conducts an investigation of sea level and its contributing processes at multiple spatial scales. Focusing on primarily interannual time-scales and data-driven approaches, new data sources and technologies are utilized to reduce current uncertainties. First, sea-level trends are assessed over the global ocean and at coastlines using data from the recently launched ICESat-2 satellite. These trends agree well with independent measurements, while also filling observational gaps along undersampled coastlines and at high-latitudes. Next, the spatial focus is narrowed to the U.S. East Coast, which is experiencing exceptionally high rates of relative sea-level rise, largely due to land subsidence. By incorporating new state-of-the-art estimates of land-ice melt, an existing Bayesian hierarchical space-time model is expanded to assess the relative contributions of sea surface height and vertical land motion to 20th century relative-sea level change. Model results confirm previous findings that identified regional-scale geological processes as the primary driver of spatial variability in East Coast relative sea level. By rigorously quantifying uncertainties, constraints are placed on the current state of knowledge with clear directions for future research. Finally, small-scale vertical land motion in Hampton Roads, VA is investigated using the remote-sensing technology of Interferometric Synthetic Aperture Radar (InSAR). Two different data sources and processing strategies are implemented which independently reveal substantial rates of vertical land motion that vary over short spatial scales. The results highlight the importance of vertical land motion in exacerbating negative impacts of relative sea-level rise such as flooding and inundation. Overall, this study leverages new spaceborne sensors, an innovative statistical model, and state-of-the-art processing strategies to enhance our understanding of ongoing sea-level change

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