Monitoring permafrost environments with Synthetic Aperture Radar (SAR) sensors

Permafrost occupies approximately 24% of the exposed land area in the Northern Hemisphere. It is an important element of the cryosphere and has strong impacts on hydrology, biological processes, land surface energy budget, and infrastructure. For several decades, surface air temperatures in the high northern latitudes have warmed at approximately twice the global rate. Permafrost temperatures have increased in most regions since the early 1980s, the averaged warming north of 60°N has been 1-2°C. In-situ measurements are essential to understanding physical processes in permafrost terrain, but they have several limitations, ranging from difficulties in drilling to the representativeness of limited single point measurements. Remote sensing is urgently needed to supplement ground-based measurements and extend the point observations to a broader spatial domain. This thesis concentrates on the sub-arctic permafrost environment monitoring with SAR datasets. The study site is selected in a typical discontinuous permafrost region in the eastern Canadian sub-Arctic. Inuit communities in Nunavik and Nunatsiavut in the Canadian eastern sub-arctic are amongst the groups most affected by the impacts of climate change and permafrost degradation. Synthetic Aperture Radar (SAR) datasets have advantages for permafrost monitoring in the Arctic and sub-arctic regions because of its high resolution and independence of cloud cover and solar illumination. To date, permafrost environment monitoring methods and strategies with SAR datasets are still under development. The variability of active layer thickness is a direct indication of permafrost thermal state changes. The Differential SAR Interferometry (D-InSAR) technique is applied in the study site to derive ground deformation, which is introduced by the thawing/freezing depth of active layer and underlying permafrost. The D-InSAR technique has been used for the mapping of ground surface deformation over large areas by interpreting the phase difference between two signals acquired at different times as ground motion information. It shows the ability to detect freeze/thaw-related ground motion over permafrost regions. However, to date, accuracy and value assessments of D-InSAR applications have focused mostly on the continuous permafrost region where the vegetation is less developed and causes fewer complicating factors for the D-InSAR application, less attention is laid on the discontinuous permafrost terrain. In this thesis, the influencing factors and application conditions for D-InSAR in the discontinuous permafrost environment are evaluated by using X- band and L-band data. Then, benefit from by the high-temporal resolution of C-band Sentinel-1 time series, the seasonal displacement is derived from small baseline subsets (SBAS)-InSAR. Landforms are indicative of permafrost presence, with their changes inferring modifications to permafrost conditions. A permafrost landscape mapping method was developed which uses multi-temporal TerraSAR-X backscatter intensity and interferometric coherence information. The land cover map is generated through the combined use of object-based image analysis (OBIA) and classification and regression tree analysis (CART). An overall accuracy of 98% is achieved when classifying rock and water bodies, and an accuracy of 79% is achieved when discriminating between different vegetation types with one year of single-polarized acquisitions. This classification strategy can be transferred to other time-series SAR datasets, e.g., Sentinel-1, and other heterogeneous environments. One predominant change in the landscape tied to the thaw of permafrost is the dynamics of thermokarst lakes. Dynamics of thermokarst lakes are developed through their lateral extent and vertical depth changes. Due to different water depth, ice cover over shallow thermokarst ponds/lakes can freeze completely to the lake bed in winter, resulting in grounded ice; while ice cover over deep thermokarst ponds/lakes cannot, which have liquid water persisting under the ice cover all winter, resulting in floating ice. Winter ice cover regimes are related to water depths and ice thickness. In the lakes having floating ice, the liquid water induces additional heat in the remaining permafrost underneath and surroundings, which contributes to further intensified permafrost thawing. SAR datasets are utilized to detect winter ice cover regimes based on the character that liquid water has a remarkably high dielectric constant, whereas pure ice has a low value. Patterns in the spatial distribution of ice-cover regimes of thermokarst ponds in a typical discontinuous permafrost region are first revealed. Then, the correlations of these ice-cover regimes with the permafrost degradation states and thermokarst pond development in two historical phases (Sheldrake catchment in the year 1957 and 2009, Tasiapik Valley 1994 and 2010) were explored. The results indicate that the ice-cover regimes of thermokarst ponds are affected by soil texture, permafrost degradation stage and permafrost depth. Permafrost degradation is difficult to directly assess from the coverage area of floating-ice ponds and the percentage of all thermokarst ponds consisting of such floating-ice ponds in a single year. Continuous monitoring of ice-cover regimes and surface areas is recommended to elucidate the hydrological trajectory of the thermokarst process. Several operational monitoring methods have been developed in this thesis work. In the meanwhile, the spatial distribution of seasonal ground thaw subsidence, permafrost landscape, thermokarst ponds and their winter ice cover regimes are first revealed in the study area. The outcomes help understand the state and dynamics of permafrost environment.Der Permafrostboden bedeckt etwa 24% der exponierten Landfläche in der nördlichen Hemisphäre. Es ist ein wichtiges Element der Kryosphäre und hat starke Auswirkungen auf die Hydrologie, die biologischen Prozesse, das Energie-Budget der Landoberfläche und die Infrastruktur. Seit mehreren Jahrzehnten erhöhen sich die Oberflächenlufttemperaturen in den nördlichen hohen Breitengraden etwa doppelt so stark wie die globale Rate. Die Temperaturen der Permafrostböden sind in den meisten Regionen seit den frühen 1980er Jahren gestiegen. Die durchschnittliche Erwärmung nördlich von 60° N beträgt 1-2°C. In-situ-Messungen sind essentiell für das Verständnis der physischen Prozesse im Permafrostgelände. Es gibt jedoch mehrere Einschränkungen, die von Schwierigkeiten beim Bohren bis hin zur Repräsentativität begrenzter Einzelpunktmessungen reichen. Fernerkundung ist dringend benötigt, um bodenbasierte Messungen zu ergänzen und punktuelle Beobachtungen auf einen breiteren räumlichen Bereich auszudehnen. Diese Dissertation konzentriert sich auf die Umweltbeobachtung der subarktischen Permafrostböden mit SAR-Datensätzen. Das Untersuchungsgebiet wurde in einer typischen diskontinuierlichen Permafrostzone in der kanadischen östlichen Sub-Arktis ausgewählt. Die Inuit-Gemeinschaften in den Regionen Nunavik und Nunatsiavut in der kanadischen östlichen Sub-Arktis gehören zu den Gruppen, die am stärksten von den Auswirkungen des Klimawandels und Permafrostdegradation betroffen sind. Synthetische Apertur Radar (SAR) Datensätze haben Vorteile für das Permafrostmonitoring in den arktischen und subarktischen Regionen aufgrund der hohen Auflösung und der Unabhängigkeit von Wolkendeckung und Sonnenstrahlung. Bis heute sind die Methoden und Strategien mit SAR-Datensätzen für Umweltbeobachtung der Permafrostböden noch in der Entwicklung. Die Variabilität der Auftautiefe der aktiven Schicht ist eine direkte Indikation der Veränderung des thermischen Zustands der Permafrostböden. Die Differential-SAR-Interferometrie(D-Insar)-Technik wird im Untersuchungsgebiet zur Ableitung der Bodendeformation, die durch Auftau- / und Gefriertiefe der aktiven Schicht und des unterliegenden Permafrostbodens eingeführt wird, eingesetzt. Die D-InSAR-Technik wurde für Kartierung der Landoberflächendeformation über große Flächen verwendet, indem der Phasenunterschied zwischen zwei zu verschiedenen Zeitpunkten als Bodenbewegungsinformation erfassten Signalen interpretiert wurde. Es zeigt die Fähigkeit, tau- und gefrierprozessbedingte Bodenbewegungen über Permafrostregionen zu detektieren. Jedoch fokussiert sich die Genauigkeit und Wertschätzung der D-InSAR-Anwendung bis heute hauptsächlich auf kontinuierliche Permafrostregion, wo die Vegetation wenig entwickelt ist und weniger komplizierte Faktoren für D-InSAR-Anwendung verursacht. Das diskontinuierliche Permafrostgelände wurde nur weniger berücksichtigt. In dieser Dissertation wurden die Einflussfaktoren und Anwendungsbedingungen für D-InSAR im diskontinuierlichen Permafrostgebiet mittels X-Band und L-Band Daten ausgewertet. Dann wurde die saisonale Verschiebung dank der hohen Auflösung der C-Band Sentinel-1 Zeitreihe von „Small Baseline Subsets (SBAS)-InSAR“ abgeleitet. Landformen weisen auf die Präsenz des Permafrosts hin, wobei deren Veränderungen auf die Modifikation der Permafrostbedingungen schließen. Eine Kartierungsmethode der Permafrostlandschaft wurde entwickelt, dabei wurde Multi-temporal TerraSAR-X Rückstreuungsintensität und interferometrische Kohärenzinformationen verwendet. Die Landbedeckungskarte wurde durch kombinierte Anwendung objektbasierter Bildanalyse (OBIA) und Klassifikations- und Regressionsbaum Analyse (CART) generiert. Eine Gesamtgenauigkeit in Höhe von 98% wurde bei Klassifikation der Gesteine und Wasserkörper erreicht. Bei Unterscheidung zwischen verschiedenen Vegetationstypen mit einem Jahr einzelpolarisierte Akquisitionen wurde eine Genauigkeit von 79% erreicht. Diese Klassifikationsstrategie kann auf andere Zeitreihen der SAR-Datensätzen, z.B. Sentinel-1, und auch anderen heterogenen Umwelten übertragen werden. Eine vorherrschende Veränderung in der Landschaft, die mit dem Auftauen des Permafrosts verbunden ist, ist die Dynamik der Thermokarstseen. Die Dynamik der Thermokarstseen ist durch Veränderungen der seitlichen Ausdehnung und der vertikalen Tiefe entwickelt. Aufgrund der unterschiedlichen Wassertiefen kann die Eisdecke über den flachen Thermokarstteichen/-seen im Winter bis auf den Wasserboden vollständig gefroren sein, was zum geerdeten Eis führt, während die Eisdecke über den tiefen Thermokarstteichen/-seen es nicht kann. In den tiefen Thermokarstteichen/-seen bleibt den ganzen Winter flüssiges Wasser unter der Eisdecke bestehen, was zum Treibeis führt. Das Wintereisdeckenregime bezieht sich auf die Wassertiefe und die Eisdicke. In den Seen mit Treibeis leitet das flüssige Wasser zusätzliche Wärme in den restlichen Permafrost darunter oder in der Umgebung, was zur weiteren Verstärkung des Permafrostauftauen beiträgt. Basiert auf den Charakter, dass das flüssige Wasser eine bemerkenswert hohe Dielektrizitätskonstante besitzt, während reines Eis einen niedrigen Wert hat, wurden die SAR Datensätzen zur Erkennung des Wintereisdeckenregimes verwendet. Zunächst wurden Schemen in der räumlichen Verteilung der Eisdeckenregimes der Thermokarstteiche in einer typischen diskontinuierlichen Permafrostregion abgeleitet. Dann wurden die Zusammenhänge dieser Eisdeckenregimes mit dem Degradationszustand des Permafrosts und der Entwicklung der Thermokarstteiche in zwei historischen Phasen (Sheldrake Einzugsgebiet in 1957 und 2009, Tasiapik Tal in 1994 und 2010) erforscht. Die Ergebnisse deuten darauf, dass die Eisdeckenregimes der Thermokarstteiche von der Bodenart, dem Degradationszustand des Permafrosts und der Permafrosttiefe beeinflusst werden. Es ist schwer, die Permafrostdegradation in einem einzelnen Jahr direkt durch den Abdeckungsbereich der Treibeis-Teiche und die Prozentzahl aller aus solchen Treibeis-Teichen bestehenden Thermokarstteiche abzuschätzen. Ein kontinuierliches Monitoring der Eisdeckenregimes und -oberflächen ist empfehlenswert, um den hydrologischen Verlauf des Thermokarstprozesses zu erläutern. In dieser Dissertation wurden mehrere operativen Monitoringsmethoden entwickelt. In der Zwischenzeit wurden die räumliche Verteilung der saisonalen Bodentauabsenkung, die Permafrostlandschaft, die Thermokarstteiche und ihre Wintereisdeckenregimes erstmals in diesem Untersuchungsgebiet aufgedeckt. Die Ergebnisse tragen dazu bei, den Zustand und die Dynamik der Permafrostumwelt zu verstehen

Innovative Techniques for the Retrieval of Earth’s Surface and Atmosphere Geophysical Parameters: Spaceborne Infrared/Microwave Combined Analyses

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Polarimetric Synthetic Aperture Radar

This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Polarimetric Synthetic Aperture Radar, Principles and Application

Demonstrates the benefits of the usage of fully polarimetric synthetic aperture radar data in applications of Earth remote sensing, with educational and development purposes. Includes numerous up-to-date examples with real data from spaceborne platforms and possibility to use a software to support lecture practicals. Reviews theoretical principles in an intuitive way for each application topic. Covers in depth five application domains (forests, agriculture, cryosphere, urban, and oceans), with reference also to hazard monitorin

Eleventh International Conference on the Bearing Capacity of Roads, Railways and Airfields

Innovations in Road, Railway and Airfield Bearing Capacity – Volume 2 comprises the second part of contributions to the 11th International Conference on Bearing Capacity of Roads, Railways and Airfields (2022). In anticipation of the event, it unveils state-of-the-art information and research on the latest policies, traffic loading measurements, in-situ measurements and condition surveys, functional testing, deflection measurement evaluation, structural performance prediction for pavements and tracks, new construction and rehabilitation design systems, frost affected areas, drainage and environmental effects, reinforcement, traditional and recycled materials, full scale testing and on case histories of road, railways and airfields. This edited work is intended for a global audience of road, railway and airfield engineers, researchers and consultants, as well as building and maintenance companies looking to further upgrade their practices in the field

Synthetic Aperture Radar (SAR) Meets Deep Learning

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