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

Reliable estimation of orbit errors in spaceborne SAR interferometry. The network approach

An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates

High-resolution deformation measurement using "Persistent Scatterer Interferometry"

Persistent Scatterer Interferometry (PSI) is a group of advanced differential interferometric SAR techniques that are used to measure and monitor terrain deformation. Different PSI techniques have been proposed in the last two decades. In this thesis, the two PSI chains implemented and used at the Geomatics division of CTTC are described: the local area PSI and the PSIG chains. The first part of the thesis is devoted to the local area PSI chain, used to analyse the deformations over small areas. The chain includes a linear deformation model to directly deal with interferometric wrapped phases. Moreover, it does not directly involve the estimation of the APS, thus simplifying the procedure and its computational cost. The chain has been tested using different types of SAR data. The availability of high resolution X-band SAR data has led to an improvement of the PSI results with respect to C-band data. The higher image resolution and phase quality implies an increase of the PS density, an improvement in the estimation precision of the residual topographic error and a higher sensibility to very small deformations, including the displacements caused by thermal dilation. An extension of the classical PSI linear deformation model has been proposed, to account for the thermal dilation effects. This allows obtaining a new PSI outcome, the thermal dilation parameter, which opens new interesting applications since it provides information on the physical properties of single objects, i.e. the coefficient of thermal expansion, and the static structures of the same objects. The second part of the thesis describes the PSIG chain, whose aim was to extend the interferometric processing to wider areas. The ability to cover wide areas is essential to obtain a unique and consistent deformation monitoring for the available SAR image full scenes, i.e. typically 30 by 50 km for TerraSAR-X, 40 by 40 km for CosmoSkyMed and 100 by 100 km for ASAR ENVISAT and ERS. This is particularly important for the forthcoming C-band Sentinel SAR data that will cover 250 by 250 km with a single image scene. The key steps of the PSIG procedure include a new selection of candidate PSs based on a phase similitude criteria and a 2+1D phase unwrapping algorithm. The procedure offers different tools to control the quality of the processing steps. It has been successfully tested over urban, rural and vegetated areas using X-band PSI data. The performance of the PSIG chain is illustrated and discussed in detail, analysing the procedure step by step.Persistent Scatterer Interferometry (PSI) és un grup de tècniques avançades d'interferometria diferencial SAR que s'utilitzen per mesurar i monitoritzar deformacions del terreny. Durant les últimes dues dècades s’han proposat diverses tècniques PSI. En aquesta tesi es descriuen les dues cadenes PSI implementades i utilitzades en la divisió de Geomàtica del CTTC: la cadena PSI d’àrea local i la cadena PSIG. La primera part de la tesi està dedicada a la cadena PSI d’àrea local, que s'utilitza per analitzar deformacions en zones d’extensió limitada. La cadena inclou un model de deformació lineal per tractar directament amb les fases interferomètriques wrapped. En canvi, no estima directament la component atmosfèrica, cosa que simplifica el procediment i el seu cost computacional. La cadena s’ha provat sobre diferents tipus de dades SAR. La disponibilitat de dades SAR d’alta resolució en banda X ha donat lloc a una millora dels resultats del PSI respecte a les dades en banda C. La resolució més gran de la imatge i la qualitat de la fase impliquen un augment de la densitat de PS, una millora en la precisió de l'estimació de l'error topogràfic residual i una sensibilitat més alta a deformacions subtils, incloent-hi els desplaçaments causats per la dilatació tèrmica. Per tenir en compte els efectes de la dilatació tèrmica, s'ha proposat una extensió del model PSI clàssic que ens permet obtenir un nou producte PSI: el paràmetre de dilatació tèrmica. Aquest paràmetre obre noves aplicacions interessants: proporciona informació relacionada amb les propietats físiques dels objectes mesurats –com el coeficient d'expansió tèrmica– i amb la seva pròpia estructura estàtica. La segona part de la tesi descriu la cadena PSIG, l'objectiu de la qual és estendre el processament interferomètric a àrees més extenses. La capacitat de cobrir àrees grans és fonamental per obtenir un únic mapa global de deformacions que sigui consistent i cobreixi l’extensió sencera de les imatges SAR disponibles, de 30 km per 50 km per TerraSAR-X, de 40 km per 40 km per CosmoSkyMed i de 100 km per 100 km per ASAR-ENVISAT i ERS. Això és particularment important tenint en compte la propera disponibilitat de les dades del satèl•lit Sentinel, que opera en banda C i cobrirà 250 km per 250 km amb una sola imatge. Els passos clau del procediment PSIG són una nova selecció de PS candidats en base a un criteri de similitud de fase i un algoritme de 2+1D phase unwrapping. El procediment ofereix diferents eines per controlar la qualitat dels diferents passos del processament. La cadena PSIG s’ha utilitzat amb èxit en àrees urbanes, rurals i amb vegetació utilitzant dades PSI en banda X. El funcionament de la cadena PSIG s'il•lustra i es descriu en detall, analitzant el procediment pas a pas

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

Land subsidence over oilfields in the Yellow River Delta

Subsidence in river deltas is a complex process that has both natural and human causes. Increasing human activities like aquaculture and petroleum extraction are affecting the Yellow River delta, and one consequence is subsidence. The purpose of this study is to measure the surface displacements in the Yellow River delta region and to investigate the corresponding subsidence source. In this paper, the Stanford Method for Persistent Scatterers (StaMPS) package was employed to process Envisat ASAR images collected between 2007 and 2010. Consistent results between two descending tracks show subsidence with a mean rate up to 30 mm/yr in the radar line of sight direction in Gudao Town (oilfield), Gudong oilfield and Xianhe Town of the delta, each of which is within the delta, and also show that subsidence is not uniform across the delta. Field investigation shows a connection between areas of non-uniform subsidence and of petroleum extraction. In a 9 km2 area of the Gudao Oilfield, a poroelastic disk reservoir model is used to model the InSAR derived displacements. In general, good fits between InSAR observations and modeled displacements are seen. The subsidence observed in the vicinity of the oilfield is thus suggested to be caused by fluid extraction

Characterizing slope instability kinematics by integrating multi-sensor satellite remote sensing observations

Over the past few decades, the occurrence and intensity of geological hazards, such as landslides, have substantially risen due to various factors, including global climate change, seismic events, rapid urbanization and other anthropogenic activities. Landslide disasters pose a significant risk in both urban and rural areas, resulting in fatalities, infrastructure damages, and economic losses. Nevertheless, conventional ground-based monitoring techniques are often costly, time-consuming, and require considerable resources. Moreover, some landslide incidents occur in remote or hazardous locations, making ground-based observation and field investigation challenging or even impossible. Fortunately, the advancements in spaceborne remote sensing technology have led to the availability of large-scale and high-quality imagery, which can be utilized for various landslide-related applications, including identification, monitoring, analysis, and prediction. This efficient and cost-effective technology allows for remote monitoring and assessment of landslide risks and can significantly contribute to disaster management and mitigation efforts. Consequently, spaceborne remote sensing techniques have become vital for geohazard management in many countries, benefiting society by providing reliable downstream services. However, substantial effort is required to ensure that such benefits are provided. For establishing long-term data archives and reliable analyses, it is essential to maintain consistent and continued use of multi-sensor spaceborne remote sensing techniques. This will enable a more thorough understanding of the physical mechanisms responsible for slope instabilities, leading to better decision-making and development of effective mitigation strategies. Ultimately, this can reduce the impact of landslide hazards on the general public. The present dissertation contributes to this effort from the following perspectives: 1. To obtain a comprehensive understanding of spaceborne remote sensing techniques for landslide monitoring, we integrated multi-sensor methods to monitor the entire life cycle of landslide dynamics. We aimed to comprehend the landslide evolution under complex cascading events by utilizing various spaceborne remote sensing techniques, e.g., the precursory deformation before catastrophic failure, co-failure procedures, and post-failure evolution of slope instability. 2. To address the discrepancies between spaceborne optical and radar imagery, we present a methodology that models four-dimensional (4D) post-failure landslide kinematics using a decaying mathematical model. This approach enables us to represent the stress relaxation for the landslide body dynamics after failure. By employing this methodology, we can overcome the weaknesses of the individual sensor in spaceborne optical and radar imaging. 3. We assessed the effectiveness of a newly designed small dihedral corner reflector for landslide monitoring. The reflector is compatible with both ascending and descending satellite orbits, while it is also suitable for applications with both high-resolution and medium-resolution satellite imagery. Furthermore, although its echoes are not as strong as those of conventional reflectors, the cost of the newly designed reflectors is reduced, with more manageable installation and maintenance. To overcome this limitation, we propose a specific selection strategy based on a probability model to identify the reflectors in satellite images

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Ground-based synthetic aperture radar (GBSAR) interferometry for deformation monitoring

Ph. D ThesisGround-based synthetic aperture radar (GBSAR), together with interferometry, represents a powerful tool for deformation monitoring. GBSAR has inherent flexibility, allowing data to be collected with adjustable temporal resolutions through either continuous or discontinuous mode. The goal of this research is to develop a framework to effectively utilise GBSAR for deformation monitoring in both modes, with the emphasis on accuracy, robustness, and real-time capability. To achieve this goal, advanced Interferometric SAR (InSAR) processing algorithms have been proposed to address existing issues in conventional interferometry for GBSAR deformation monitoring. The proposed interferometric algorithms include a new non-local method for the accurate estimation of coherence and interferometric phase, a new approach to selecting coherent pixels with the aim of maximising the density of selected pixels and optimizing the reliability of time series analysis, and a rigorous model for the correction of atmospheric and repositioning errors. On the basis of these algorithms, two complete interferometric processing chains have been developed: one for continuous and the other for discontinuous GBSAR deformation monitoring. The continuous chain is able to process infinite incoming images in real time and extract the evolution of surface movements through temporally coherent pixels. The discontinuous chain integrates additional automatic coregistration of images and correction of repositioning errors between different campaigns. Successful deformation monitoring applications have been completed, including three continuous (a dune, a bridge, and a coastal cliff) and one discontinuous (a hillside), which have demonstrated the feasibility and effectiveness of the presented algorithms and chains for high-accuracy GBSAR interferometric measurement. Significant deformation signals were detected from the three continuous applications and no deformation from the discontinuous. The achieved results are justified quantitatively via a defined precision indicator for the time series estimation and validated qualitatively via a priori knowledge of these observing sites.China Scholarship Council (CSC), Newcastle Universit

Ground Surface Subsidence Monitoring Using Sentinel-1 in the “Kostolac” Open Pit Coal Mine

Open pit coal mining affects surrounding populated areas, resulting in terrain surface deformation. Surface deformation should be monitored as often as possible to control deformations and prevent potential incidents. This paper analyzes time series deformation estimated from the Sentinel-1 satellite images using the Persistent Scatterer Interferometry method to monitor subsidence rates caused by open pit mining activities. It is possible to measure deformations using classical geodetic methods, but those are rarely used in practice because they are time-consuming and expensive for application in large areas. Using the open access radar images from the Sentinel-1 mission, 513 images from the repository were downloaded between October 2016 and the end of December 2020. We present the processing steps in detail in order to establish a workflow for the automated processing of vertical displacement estimation using open source tools; a total of 402 images were processed: 215 images belonged to the ascending satellite orbit, 187 images belonged to the descending orbit, and 111 images were rejected because of adverse weather conditions. The PS InSAR technique has never been used for the mines of the Republic of Serbia or for land surveying practices related to deformation monitoring. The results based on the Sentinel-1 images were compared with results from geodetic leveling and with neotectonic uplift trends. The trend lines of vertical displacement obtained from PS and corresponding leveling are significantly similar (a Pearson correlation of 85% with a p-value of 0.015). The final evaluation reported results of vertical displacements at the leveling benchmark of −3.4 mm/year with the PS InSAR method and −2.7 mm/year with the leveling method. A comparison of the PS vertical displacements with a settlement model fits reasonably, suggesting that the measurements are valid. As four years of PS time series data is insufficient to establish undisputable conclusions on the neotectonics uplift, extending the time series (covering at least a decade) implies that this approach will become attractive in future neotectonic uplift trend estimations. This study illustrates not only the ability of Sentinel-1 data in mapping vertical deformations, but the obtained results could also be used for geohazard monitoring and land monitoring in general for the area of interest