143 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 ErdoberflĂ€che aus dem Weltraum. Sie basiert auf der Identifizierung und Analyse von stabilen Punktstreuern (sog. Persistent Scatterer, PS) durch die Anwendung von AnsĂ€tzen der Zeitreihenanalyse auf Stapel von SAR-Interferogrammen. PS Punkte dominieren die RĂŒckstreuung der Auflösungszellen, in denen sie sich befinden, und werden durch geringfĂŒgige Dekorrelation charakterisiert. Verschiebungen solcher PS Punkte können mit einer potenziellen Submillimetergenauigkeit ĂŒberwacht 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 fĂŒr die Methode. Physische VerĂ€nderungen der LandoberflĂ€che und Änderungen in der Aufnahmegeometrie können dazu fĂŒhren, dass PS Punkte im Laufe der Zeit erscheinen oder verschwinden. Die Anzahl der kontinuierlich kohĂ€renten PS Punkte nimmt mit zunehmender LĂ€nge der Zeitreihen ab, wĂ€hrend die Anzahl der TPS Punkte zunimmt, die nur wĂ€hrend eines oder mehrerer getrennter Segmente der analysierten Zeitreihe kohĂ€rent sind. Daher ist es wĂŒnschenswert, die Analyse solcher TPS Punkte in die PSI zu integrieren, um ein flexibles PSI-System zu entwickeln, das in der Lage ist mit dynamischen VerĂ€nderungen der LandoberflĂ€che umzugehen und somit ein kontinuierliches Verschiebungsmonitoring ermöglicht. Eine weitere Herausforderung der PSI besteht darin, großflĂ€chiges Monitoring in Regionen mit komplexen atmosphĂ€rischen Bedingungen durchzufĂŒhren. Letztere fĂŒhren zu hoher Unsicherheit in den Verschiebungszeitreihen bei großen AbstĂ€nden zur rĂ€umlichen 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 prĂ€sentiert, die TPS Punkte vollstĂ€ndig in die PSI integriert. In Evaluierungsstudien mit echten SAR Daten wird gezeigt, dass die Integration von TPS Punkten tatsĂ€chlich die BewĂ€ltigung dynamischer VerĂ€nderungen der LandoberflĂ€che ermöglicht und mit zunehmender ZeitreihenlĂ€nge zunehmende Relevanz fĂŒr PSI-basierte Beobachtungsnetzwerke hat. Der zweite Hauptbeitrag ist die Vorstellung einer Methode zur kovarianzbasierten Referenzintegration in großflĂ€chige PSI-Anwendungen zur SchĂ€tzung von rĂ€umlich korreliertem Rauschen. Die Methode basiert auf der Abtastung des Rauschens an Referenzpixeln mit bekannten Verschiebungszeitreihen und anschließender Interpolation auf die restlichen PS Pixel unter BerĂŒcksichtigung der rĂ€umlichen Statistik des Rauschens. Es wird in einer Simulationsstudie sowie einer Studie mit realen Daten gezeigt, dass die Methode ĂŒberlegene Leistung im Vergleich zu alternativen Methoden zur Reduktion von rĂ€umlich 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 geschĂ€tzten Landsenkungsraten zeigen eine hohe VariabilitĂ€t auf kurzen sowie großen rĂ€umlichen Skalen. Die höchsten Senkungsraten von bis zu 6 cm pro Jahr treten hauptsĂ€chlich in stĂ€dtischen Gebieten auf. Es kann gezeigt werden, dass der grĂ¶ĂŸte Teil der Landsenkung ihren Ursprung im oberflĂ€chennahen Untergrund hat. Die prĂ€sentierte Methode zur Reduzierung von rĂ€umlich korreliertem Rauschen verbessert die Ergebnisse signifikant, wenn eine angemessene rĂ€umliche Verteilung von Referenzgebieten verfĂŒgbar ist. In diesem Fall wird das Rauschen effektiv reduziert und unabhĂ€ngige Ergebnisse von zwei Interferogrammstapeln, die aus unterschiedlichen Orbits aufgenommen wurden, zeigen große Übereinstimmung. Die Integration von TPS Punkten fĂŒhrt fĂŒr die analysierte Zeitreihe von sechs Jahren zu einer deutlich grĂ¶ĂŸeren 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 anfĂ€ngliche Bewegungszeitreihen zu analysieren

    Geodetic monitoring of complex shaped infrastructures using Ground-Based InSAR

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    In the context of climate change, alternatives to fossil energies need to be used as much as possible to produce electricity. Hydroelectric power generation through the utilisation of dams stands out as an exemplar of highly effective methodologies in this endeavour. Various monitoring sensors can be installed with different characteristics w.r.t. spatial resolution, temporal resolution and accuracy to assess their safe usage. Among the array of techniques available, it is noteworthy that ground-based synthetic aperture radar (GB-SAR) has not yet been widely adopted for this purpose. Despite its remarkable equilibrium between the aforementioned attributes, its sensitivity to atmospheric disruptions, specific acquisition geometry, and the requisite for phase unwrapping collectively contribute to constraining its usage. Several processing strategies are developed in this thesis to capitalise on all the opportunities of GB-SAR systems, such as continuous, flexible and autonomous observation combined with high resolutions and accuracy. The first challenge that needs to be solved is to accurately localise and estimate the azimuth of the GB-SAR to improve the geocoding of the image in the subsequent step. A ray tracing algorithm and tomographic techniques are used to recover these external parameters of the sensors. The introduction of corner reflectors for validation purposes confirms a significant error reduction. However, for the subsequent geocoding, challenges persist in scenarios involving vertical structures due to foreshortening and layover, which notably compromise the geocoding quality of the observed points. These issues arise when multiple points at varying elevations are encapsulated within a singular resolution cell, posing difficulties in pinpointing the precise location of the scattering point responsible for signal return. To surmount these hurdles, a Bayesian approach grounded in intensity models is formulated, offering a tool to enhance the accuracy of the geocoding process. The validation is assessed on a dam in the black forest in Germany, characterised by a very specific structure. The second part of this thesis is focused on the feasibility of using GB-SAR systems for long-term geodetic monitoring of large structures. A first assessment is made by testing large temporal baselines between acquisitions for epoch-wise monitoring. Due to large displacements, the phase unwrapping can not recover all the information. An improvement is made by adapting the geometry of the signal processing with the principal component analysis. The main case study consists of several campaigns from different stations at Enguri Dam in Georgia. The consistency of the estimated displacement map is assessed by comparing it to a numerical model calibrated on the plumblines data. It exhibits a strong agreement between the two results and comforts the usage of GB-SAR for epoch-wise monitoring, as it can measure several thousand points on the dam. It also exhibits the possibility of detecting local anomalies in the numerical model. Finally, the instrument has been installed for continuous monitoring for over two years at Enguri Dam. An adequate flowchart is developed to eliminate the drift happening with classical interferometric algorithms to achieve the accuracy required for geodetic monitoring. The analysis of the obtained time series confirms a very plausible result with classical parametric models of dam deformations. Moreover, the results of this processing strategy are also confronted with the numerical model and demonstrate a high consistency. The final comforting result is the comparison of the GB-SAR time series with the output from four GNSS stations installed on the dam crest. The developed algorithms and methods increase the capabilities of the GB-SAR for dam monitoring in different configurations. It can be a valuable and precious supplement to other classical sensors for long-term geodetic observation purposes as well as short-term monitoring in cases of particular dam operations

    Synthetic Aperture Radar (SAR) Meets Deep Learning

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    This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports

    Spatio-temporal analysis of coastal sediment erosion in Cape Town through remote sensing and geoinformation science

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    Coastal erosion can be described as the landward or seaward propagation of coastlines. Coastal processes occur over various space and time scales, limiting in-situ approaches of monitoring change. As such it is imperative to take advantage of multisensory, multi-scale and multi-temporal modern spatial technologies for multi-dimensional coastline change monitoring. The research presented here intends to showcase the synergy amongst remote sensing techniques by showcasing the use of coastal indicators towards shoreline assessment over the Kommetjie and Milnerton areas along the Cape Town coastline. There has been little progress in coastal studies in the Western Cape that encompass the diverse and dynamic aspects of coastal environments and in particular, sediment movement. Cape Town, in particular; is socioeconomically diverse and spatially segregated, with heavy dependence on its 240km of coastline. It faces sea level rise intensified by real-estate development close to the high-water mark and on reclaimed land. Spectral indices and classification techniques are explored to accommodate the complex bio-optical properties of coastal zones. This allows for the segmentation of land and ocean components to extract shorelines from multispectral Landsat imagery for a long term (1991-2021) shoreline assessment. The DSAS tool used these extracted shorelines to quantify shoreline change and was able to determine an overall averaged erosional rate of 2.56m/yr. for Kommetjie and 2.35m/yr. for Milnerton. Beach elevation modelling was also included to evaluate short term (2016-2021) sediment volumetric changes by applying Differential Interferometry to Sentinel-1 SLC data and the Waterline method through a combination of Sentinel -1 GRD and tide gauge data. The accuracy, validation and correction of these elevation models was conducted at the pixel level by comparison to an in-field RTK GPS survey used to capture the current state of the beaches. The results depict a sediment deficit in Kommetjie whilst accretion is prevalent along the Milnerton coastline. Shoreline propagation and coastal erosion quantification leads to a better understanding of geomorphology, hydrodynamic and land use influences on coastlines. This further informs climate adaptation strategies, urban planning and can support further development of interactive coastal information systems

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

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    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

    Land Surface Monitoring Based on Satellite Imagery

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    This book focuses attention on significant novel approaches developed to monitor land surface by exploiting satellite data in the infrared and visible ranges. Unlike in situ measurements, satellite data provide global coverage and higher temporal resolution, with very accurate retrievals of land parameters. This is fundamental in the study of climate change and global warming. The authors offer an overview of different methodologies to retrieve land surface parameters— evapotranspiration, emissivity contrast and water deficit indices, land subsidence, leaf area index, vegetation height, and crop coefficient—all of which play a significant role in the study of land cover, land use, monitoring of vegetation and soil water stress, as well as early warning and detection of forest ïŹres and drought

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

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    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

    The Fifteenth Marcel Grossmann Meeting

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    The three volumes of the proceedings of MG15 give a broad view of all aspects of gravitational physics and astrophysics, from mathematical issues to recent observations and experiments. The scientific program of the meeting included 40 morning plenary talks over 6 days, 5 evening popular talks and nearly 100 parallel sessions on 71 topics spread over 4 afternoons. These proceedings are a representative sample of the very many oral and poster presentations made at the meeting.Part A contains plenary and review articles and the contributions from some parallel sessions, while Parts B and C consist of those from the remaining parallel sessions. The contents range from the mathematical foundations of classical and quantum gravitational theories including recent developments in string theory, to precision tests of general relativity including progress towards the detection of gravitational waves, and from supernova cosmology to relativistic astrophysics, including topics such as gamma ray bursts, black hole physics both in our galaxy and in active galactic nuclei in other galaxies, and neutron star, pulsar and white dwarf astrophysics. Parallel sessions touch on dark matter, neutrinos, X-ray sources, astrophysical black holes, neutron stars, white dwarfs, binary systems, radiative transfer, accretion disks, quasars, gamma ray bursts, supernovas, alternative gravitational theories, perturbations of collapsed objects, analog models, black hole thermodynamics, numerical relativity, gravitational lensing, large scale structure, observational cosmology, early universe models and cosmic microwave background anisotropies, inhomogeneous cosmology, inflation, global structure, singularities, chaos, Einstein-Maxwell systems, wormholes, exact solutions of Einstein's equations, gravitational waves, gravitational wave detectors and data analysis, precision gravitational measurements, quantum gravity and loop quantum gravity, quantum cosmology, strings and branes, self-gravitating systems, gamma ray astronomy, cosmic rays and the history of general relativity

    ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications

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    Twelve edited original papers on the latest and state-of-art results of topics ranging from calibration, validation, and science to a wide range of applications using ALOS-2/PALSAR-2. We hope you will find them useful for your future research
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