Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Long-term flood-hazard modeling for coastal areas using InSAR measurements and a hydrodynamic model: The case study of Lingang New City, Shanghai

In this paper, we study long-term coastal flood risk of Lingang New City, Shanghai, considering 100- and 1000-year coastal flood return periods, local seal-level rise projections, and long-term ground subsidence projections. TanDEM-X satellite data acquired in 2012 were used to generate a high-resolution topography map, and multi-sensor InSAR displacement time-series were used to obtain ground deformation rates between 2007 and 2017. Both data sets were then used to project ground deformation rates for the 2030s and 2050s. A 2-D flood inundation model (FloodMap-Inertial) was employed to predict coastal flood inundation for both scenarios. The results suggest that the sea-level rise, along with land subsidence, could result in minor but non-linear impacts on coastal inundation over time. The flood risk will primarily be determined by future exposure and vulnerability of population and property in the floodplain. Although the flood risk estimates show some uncertainties, particularly for long-term predictions, the methodology presented here could be applied to other coastal areas where sea level rise and land subsidence are evolving in the context of climate change and urbanization

Volcano monitoring with bistatic TanDEM-X SAR interferometry

Das Ziel der Dissertation ist die Untersuchung der Nutzbarkeit der Daten der TanDEM-X-Satellitenmission in der Vulkanforschung. Dabei wird die Topographie vor, während und nach einem vulkanologischen Ereignis abgebildet. Anhand einer differentiellen Analyse der abgeleiteten DEMs können topographische und volumetrische Änderungen quantifiziert werden. Als Untersuchungsgebiete dienen der Merapi in Indonesien, der Volcán de Colima in Mexico und der Tolbachik in Kamtschatka, Russland

GNSS-based Position and Baseline Determination and Simultaneous Clock Synchronization for Multistatic Synthetic Aperture Radar Constellations

Multistatic constellations can offer various advantages for SAR remote sensing. These concepts are challenging to implement for a series of technical difficulties. The lack of synchronization, caused by the operation of transmitter and receiver with different master clocks, poses one of the fundamental operational problems, contaminating the phase signatures of the radar imaging and challenging its differential ranging accuracy. In addition, baseline accuracy of a few milimeters must achieved, preferrably using data obtained from low-cost GNSS receivers. In this work, we evaluate a synchronization method based on GNSS navigation data and Precise Orbit Determination. The method consists in using in each satellite the same oscillator for the master clock of the GNSS receiver and of the SAR payload, so that the relative time estimation obtained in the precise orbit determination can be used to synchronize the radar data in the post-processing. The simulations suggest the proposed approach is capable of delivering reliable estimates of phase errors in the absence of strong baseline velocity deviations and if multipath and other systematic errors are successfully suppressed or calibrated. In addition, different configurations are evaluate in an attempt to improve the individual baselines estimates by combining GNSS data from several satellites flying in close formation. The preliminary studies indicate that the individual baseline can potentially be improved by using intersatellite links and by implementing a consistency check by comparing the height biases between DEMs generated from different pairs of satellite

On the use of COSMO/SkyMed data and Weather Models for interferometric DEM generation

AbstractThis work experiments the potentialities of COSMO/SkyMed (CSK) data in providing interferometric Digital Elevation Model (DEM). We processed a stack of CSK data for measuring with meter accuracy the ground elevation on the available coherent targets, and used these values to check the accuracy of DEMs derived from 5 tandem-like CSK pairs. In order to suppress the atmospheric signal we experimented a classical spatial filtering of the differential phase as well as the use of numerical weather prediction (NWP) model RAMS. Tandem-like pairs with normal baselines higher than 300 m allows to derive DEMs fulfilling the HRTI Level 3 specifications on the relative vertical accuracy, while the use of NWP models still seems unfeasible especially for X-band

Radar Backscatter Modeling Based on Global TanDEM-X Mission Data

Radarrückstreuung bezeichnet den Teil eines ausgesendeten elektromagnetischen Signals, der von einem Ziel am Boden wieder zurück zur Antenne gerichtet ist. Die Eigenschaften des zurückgestreuten Signals ändern sich in Abhängigkeit von Frequenz und Polarisation des Radarsignals, der Aufnahmegeometrie, sowie vom Zustand des Erdbodens und der Art der Bodenbedeckung. Informationen über das Radarrückstreuverhalten sind von höchster Wichtigkeit für die Auslegung von SAR-Missionen und werden verbreitet zur Entwicklung wissenschaftlicher Modelle genutzt, beispielsweise bei der Erforschung der Biosphäre und Kryosphäre. Hauptziel dieser Arbeit ist die Auswertung und Nutzung des globalen TanDEM-X-Datensatzes zur Modellierung der Radarrückstreuung im X-Band unter Berücksichtigung unterschiedlicher Aufnahmeparameter und Landnutzungsarten, sowie die Bereitstellung einer Reihe von globalen Rückstreumodellen, die auf aktuellen Daten basieren, für die wissenschaftliche Gemeinschaft. Es wurde ein neuer Ansatz zur statistischen Modellierung der Rückstreuinformation entwickelt, der die Qualität der zugrunde liegenden Messungen berücksichtigt. Daraus ergeben sich gewichtete polynomiale Modelle für die verschiedenen Landnutzungsarten, wie sie in der GlobCover-Karte der ESA definiert sind. Darüber hinaus wird ein eigener Validierungsansatz vorgestellt, mit zusätzlicher Betrachtung der saisonalen Variation der Rückstreuung und einer separaten Analyse des Rückstreuverhaltens des Tropischen Regenwaldes. Der nächste Schwerpunkt ist die Betrachtung des Grönländischen Eisschildes, das gekennzeichnet ist durch das Vorhandensein verschiedener Arten von Schneebedeckung, die von trockenem bis hin zu sehr feuchtem Schnee variiert. Der begrenzte Detailgrad, den die GlobCover Karte in Grönland aufweist (nur eine Klasse für das gesamte Eisschild), erlaubt dort keine verlässliche Modellierung der Rückstreuung. Diese Schwierigkeit lieferte die Motivation für die Entwicklung eines neuen Ansatzes zur Analyse des Informationsgehalts der interferometrischen TanDEM-X-Daten mit dem Ziel, unterschiedliche Schnee-Fazien mit Hilfe des sog. C-Means Fuzzy Clustering Algorithmus zu lokalisieren. Aus dieser Untersuchung konnte die Existenz von vier unterschiedlichen Klassen von Schnee-Fazien abgeleitet werden, deren Eigenschaften anschließend mit Hilfe externer Referenzdaten interpretiert wurden. Die daraus entstandene Karte wurde zur Erstellung eines einfallswinkelabhängigen Rückstreumodells genutzt, separat für jede der vier Klassen, wobei eine modifizierte Version des entwickelten Algorithmus zur Generierung globaler Rückstreumodelle eingesetzt wurde. Darüber hinaus wurde als Nebenprodukt zusätzlich die Eindringtiefe von TanDEM-X in die Eisschicht geschätzt, durch Inversion des von Weber Hoen und Zebker vorgeschlagenen "Ein-chicht Volumendekorrelationsmodells". Die Ergebnisse wurden mit dem Höhenunterschied zwischen dem globalen TanDEM-X-DEM und ICESat-Messungen verglichen. Abschließend wird ein neu entwickelter Algorithmus zur Generierung von Rückstreukarten großer Gebiete vorgestellt. Dieser erlaubt unter Verwendung von Rückstreumodellen das Angleichen der erstellten Karten anhand eines Referenzeinfallswinkels, was dann das Füllen verbleibender Lücken ermöglicht, die aufgrund fehlender Eingangsdaten vorhanden sind

Exploring bistatic scattering modeling for land surface applications using radio spectrum recycling in the Signal of Opportunity Coherent Bistatic Simulator

The potential for high spatio-temporal resolution microwave measurements has urged the adoption of the signals of opportunity (SoOp) passive radar technique for use in remote sensing. Recent trends in particular target highly complex remote sensing problems such as root-zone soil moisture and snow water equivalent. This dissertation explores the continued open-sourcing of the SoOp coherent bistatic scattering model (SCoBi) and its use in soil moisture sensing applications. Starting from ground-based applications, the feasibility of root-zone soil moisture remote sensing is assessed using available SoOp resources below L-band. A modularized, spaceborne model is then developed to simulate land-surface scattering and delay-Doppler maps over the available spectrum of SoOp resources. The simulation tools are intended to provide insights for future spaceborne modeling pursuits

Multi-sensor techniques for the measurement of post eruptive volcanic deformation and depositional features

Thesis (Ph.D.) University of Alaska Fairbanks, 2019Remote sensing of volcanic activity is an increasingly important tool for scientific investigation, hazard mitigation, and geophysical analysis. These studies were conducted to determine how combining remote sensing data in a multi-sensor analysis can improve our understanding of volcanic activity, depositional behavior, and the evolutionary history of past eruptive episodes. In a series of three studies, (1) optical photogrammetry and synthetic aperture radar are combined to determine volumes of lahars and lava dome growth at Redoubt Volcano, Alaska; (2) applied data from multiple synthetic aperture radar platforms are combined to model long-term deposition of pyroclastic flow deposits, including past deposits underlying current, observable pyroclastic flow deposits at Augustine Volcano, Alaska; and finally (3) combined, low-spatial-resolution thermal data from Advanced Very High Resolution Radiometer sensors are combined with high resolution digital elevation models derived from the microwave TanDEM-X mission, to increase the accuracy of eruption profiles and effusion rates at Tolbachik Volcano on the Kamchatka Peninsula, Russian Far East. As a result of this study, the very diverse capabilities of multiple remote sensing instruments were combined to improve the understanding of volcanic processes at three separate locations with recent eruptive activity, and to develop new methods of measurement and estimation by merging the capabilities of optical, thermal, and microwave observations. With the multi-sensor frameworks developed in this study now in place, future efforts should focus on increasing the diversity of sensor types in joint analyses, with the objective of obtaining better solutions to geophysical questions