2,254 research outputs found

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

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    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

    Flood dynamics derived from video remote sensing

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    Flooding is by far the most pervasive natural hazard, with the human impacts of floods expected to worsen in the coming decades due to climate change. Hydraulic models are a key tool for understanding flood dynamics and play a pivotal role in unravelling the processes that occur during a flood event, including inundation flow patterns and velocities. In the realm of river basin dynamics, video remote sensing is emerging as a transformative tool that can offer insights into flow dynamics and thus, together with other remotely sensed data, has the potential to be deployed to estimate discharge. Moreover, the integration of video remote sensing data with hydraulic models offers a pivotal opportunity to enhance the predictive capacity of these models. Hydraulic models are traditionally built with accurate terrain, flow and bathymetric data and are often calibrated and validated using observed data to obtain meaningful and actionable model predictions. Data for accurately calibrating and validating hydraulic models are not always available, leaving the assessment of the predictive capabilities of some models deployed in flood risk management in question. Recent advances in remote sensing have heralded the availability of vast video datasets of high resolution. The parallel evolution of computing capabilities, coupled with advancements in artificial intelligence are enabling the processing of data at unprecedented scales and complexities, allowing us to glean meaningful insights into datasets that can be integrated with hydraulic models. The aims of the research presented in this thesis were twofold. The first aim was to evaluate and explore the potential applications of video from air- and space-borne platforms to comprehensively calibrate and validate two-dimensional hydraulic models. The second aim was to estimate river discharge using satellite video combined with high resolution topographic data. In the first of three empirical chapters, non-intrusive image velocimetry techniques were employed to estimate river surface velocities in a rural catchment. For the first time, a 2D hydraulicvmodel was fully calibrated and validated using velocities derived from Unpiloted Aerial Vehicle (UAV) image velocimetry approaches. This highlighted the value of these data in mitigating the limitations associated with traditional data sources used in parameterizing two-dimensional hydraulic models. This finding inspired the subsequent chapter where river surface velocities, derived using Large Scale Particle Image Velocimetry (LSPIV), and flood extents, derived using deep neural network-based segmentation, were extracted from satellite video and used to rigorously assess the skill of a two-dimensional hydraulic model. Harnessing the ability of deep neural networks to learn complex features and deliver accurate and contextually informed flood segmentation, the potential value of satellite video for validating two dimensional hydraulic model simulations is exhibited. In the final empirical chapter, the convergence of satellite video imagery and high-resolution topographical data bridges the gap between visual observations and quantitative measurements by enabling the direct extraction of velocities from video imagery, which is used to estimate river discharge. Overall, this thesis demonstrates the significant potential of emerging video-based remote sensing datasets and offers approaches for integrating these data into hydraulic modelling and discharge estimation practice. The incorporation of LSPIV techniques into flood modelling workflows signifies a methodological progression, especially in areas lacking robust data collection infrastructure. Satellite video remote sensing heralds a major step forward in our ability to observe river dynamics in real time, with potentially significant implications in the domain of flood modelling science

    Seasonal and Multi-year Variability of Ice Dynamics of South Croker Bay Glacier, Devon Ice Cap, Canadian Arctic from 2015 to 2021

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    The effects of climate change have already been observed across the globe, impacting weather, ecosystems, and society. These effects have been most pronounced in polar regions, which experience warming at a faster rate than other latitudes due to positive feedbacks resulting from reduced ice and snow cover. Compared to the 1.1oC of warming around the globe since the 1980s, the Arctic has warmed by 3oC. Glaciers and ice caps are of particular concern as they have profound impacts on water resources, shipping and travel routes, and global sea level rise. As such, glacier dynamics play a key role in understanding effects on the global system. The Canadian High Arctic in particular has doubled in rates of mass loss since the 1990s, which is of great concern as it is the third largest contributor to global sea level rise after Antarctica and Greenland. While glacier flow within the region has been studied, some glaciers have been observed to not align with current understandings of dynamics. The subject of this study, South Croker Bay Glacier, located on Devon Ice Cap in Nunavut, Canada has exhibited velocity variability on oscillating temporal scales which do not align with surging, pulsing, or consistent acceleration explanations. The primary objective of this thesis was to create a dense record of velocities derived from TerraSAR-X imagery every 11 days from 2015 to 2021 to gain insight into seasonal and multi-annual velocity variability. As a result, a near-continuous velocity record of South Croker Bay Glacier has been created, highlighting a shift in velocities which occurred during the winter of 2018/19. The second objective was to explore the potential drivers of the observed velocity variability, which were hydrology, sea ice buttressing, and bed topography. Looking at the spatial propagation of acceleration and terminus position as well, it is concluded that the variability is not driven by surge- or pulse-type mechanisms. Instead, it is suggested that the driver of the observed variability on the glacier is the result of the evolving configuration of the hydrological network. This is supported by surface air temperature and surface lake area records during the study period. Finally, the third objective was to assess the feasibility of utilizing remote sensing for seasonal variability detection. Based on the analysis, the method was successful in the proposed objectives, creating a record of velocities that was not previously available for South Croker Bay Glacier

    Satellite remote sensing of surface winds, waves, and currents: Where are we now?

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    This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields

    National Report for the IAG of the IUGG 2019-2022

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    Major results of researches conducted by Russian geodesists in 2019-2022 on the topics of the International Association of Geodesy (IAG) of the International Union of Geodesy and Geophysics (IUGG) are presented in this issue. This report is prepared by the Section of Geodesy of the National Geophysical Committee of Russia. In the report prepared for the XXVII General Assembly of IUGG (Germany, Berlin, 11-20 July 2023), the results of principal researches in geodesy, geodynamics, gravimetry, in the studies of geodetic reference frame creation and development, Earth's shape and gravity field, Earth's rotation, geodetic theory, its application and some other directions are briefly described. For some objective reasons not all results obtained by Russian scientists on the field of geodesy are included in the report.Comment: Misprint in the title of the arXiv record has been corrected. The submission content is not affecte

    Empleo de agrupaciones estadísticas en los estudios geodinámicos multiescala

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    El conocimiento de la cinemática de la corteza terrestre puede estudiarse con precisión mediante técnicas que determinen los desplazamientos superficiales, siempre con un periodo de tiempo mínimo de 5 años, lo que provoca trabajar con un número ingente de datos. La investigación desarrollada en esta Tesis Doctoral se ha centrado en buscar técnicas que ayuden a discriminar comportamientos geodinámicos en las diferentes escalas de estudio, presentando tres trabajos según: i) Un enfoque global-regional de la región de la Macaronesia: empleando estaciones GNSS continuas en un periodo temporal de 15 años. Con la ayuda de las agrupaciones de datos y los mapas de esfuerzo/cizalla se identificaron claramente los límites tectónicos de la zona denominada Macaronesia, validando su uso global, así como apoyar con estos resultados, la posible existencia de una zona de corte intraplaca entre las islas Canarias y la Península Ibérica. ii) Una visión regional-local de la isla de Tenerife (Islas Canarias): durante 10 años de observaciones en estaciones GNSS continuas y episódicas por campañas, analizados nuevamente por las mismas metodologías mencionadas en i). El análisis de conglomerados identificó valores locales anómalos en una estación y aclaró, junto a los resultados del análisis de esfuerzos, la identificación de dos dinámicas regionales en la isla. Asimismo, la tendencia direccional general de los residuales, respecto a la estación de referencia de Gran Canaria, hizo posible ver, por primera vez, el efecto de la dinámica regional de una zona de corte con gran sismicidad entre ambas islas, que parece indicar el acercamiento de estas islas. iii) Un último enfoque que emplea de nuevo la escala regional-local en Tenerife: pero centrado en esta ocasión en la dinámica vertical, empleando datos derivados de técnicas de interferometría con Radar de Apertura Sintética (SAR) durante 6 años, obteniendo agrupaciones de anomalías cinemáticas en la isla según el estadístico geoespacial Gi* de Getis-Ord. Se obtuvieron delimitaciones locales con valores anómalos para la cinemática vertical que mostraron los efectos derivados de la sobreexplotación de los recursos hídricos subterráneos en toda la isla, sin encontrar ningún efecto regional relacionados con la actividad volcánica de la isla. En todos los casos propuestos se han empleado distintas técnicas de agrupación de datos que han ayudado a mejorar la interpretación de los resultados derivados del tratamiento de grandes cantidades de datos de deformación terrestre, vinculados a las tecnologías espaciales GNSS y geoespaciales procedentes de la interferometría radar multitemporal

    Automatic wide area land cover mapping using Sentinel-1 multitemporal data

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    This study introduces a methodology for land cover mapping across extensive areas, utilizing multitemporal Sentinel-1 Synthetic Aperture Radar (SAR) data. The objective is to effectively process SAR data to extract spatio-temporal features that encapsulate temporal patterns within various land cover classes. The paper outlines the approach for processing multitemporal SAR data and presents an innovative technique for the selection of training points from an existing Medium Resolution Land Cover (MRLC) map. The methodology was tested across four distinct regions of interest, each spanning 100 × 100 km2, located in Siberia, Italy, Brazil, and Africa. These regions were chosen to evaluate the methodology’s applicability in diverse climate environments. The study reports both qualitative and quantitative results, showcasing the validity of the proposed procedure and the potential of SAR data for land cover mapping. The experimental outcomes demonstrate an average increase of 16% in overall accuracy compared to existing global products. The results suggest that the presented approach holds promise for enhancing land cover mapping accuracy, particularly when applied to extensive areas with varying land cover classes and environmental conditions. The ability to leverage multitemporal SAR data for this purpose opens new possibilities for improving global land cover maps and their applications

    Deep Learning for Subtle Volcanic Deformation Detection With InSAR Data in Central Volcanic Zone

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    Subtle volcanic deformations point to volcanic activities, and monitoring them helps predict eruptions. Today, it is possible to remotely detect volcanic deformation in mm/year scale thanks to advances in interferometric synthetic aperture radar (InSAR). This article proposes a framework based on a deep learning model to automatically discriminate subtle volcanic deformations from other deformation types in five-year-long InSAR stacks. Models are trained on a synthetic training set. To better understand and improve the models, explainable artificial intelligence (AI) analyses are performed. In initial models, Gradient-weighted Class Activation Mapping (Grad-CAM) linked new-found patterns of slope processes and salt lake deformations to false-positive detections. The models are then improved by fine-tuning (FT) with a hybrid synthetic-real data, and additional performance is extracted by low-pass spatial filtering (LSF) of the real test set. The t-distributed stochastic neighbor embedding (t-SNE) latent feature visualization confirmed the similarity and shortcomings of the FT set, highlighting the problem of elevation components in residual tropospheric noise. After fine-tuning, all the volcanic deformations are detected, including the smallest one, Lazufre, deforming 5 mm/year. The first time confirmed deformation of Cerro El Condor is observed, deforming 9.9–17.5 mm/year. Finally, sensitivity analysis uncovered the model’s minimal detectable deformation of 2 mm/year

    Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data

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    Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea-level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing strategies. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods, but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty in order to enhance inter-comparison and empower physical process insights across glacier elevation-change studies

    The Potential of New LiDAR Datasets for Archaeology in Switzerland

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    LiDAR and its derived elevation models have revolutionized archaeological research in forested areas around the globe. Almost a third of Switzerland is covered in forests. The number of archaeological sites recorded in forests in Switzerland is, however, limited. Given these circumstances, it is surprising how underutilized LiDAR data are in archaeological research in the country. As the Federal Office of Topography swisstopo is finalizing the acquisition of new LiDAR datasets, increasing the covered area and allowing for limited time series analyses, these data should be used to the fullest extent. This article describes the open access datasets and elaborates on their potential for archaeological research and cultural heritage management. By employing LiDAR data on a large scale, Swiss archaeological research would likely substantially increase the number of recorded heritage sites. Additionally, this will have the effect of complementing the palimpsests of past anthropogenic activity throughout the landscape while reducing survey biases in the archaeological record
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