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

Applications of SAR Interferometry in Earth and Environmental Science Research

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions

Synthetic Aperture Radar für Monitoring in städtischen Gebieten und im Bergbau

Considering it is hazardous to the environment and people, monitoring land movements at urban area become more and more significant. On the other hand, studying of land movements in non-urban area is also important. Synthetic aperture radar using interferometric technique, which is known as InSAR, is capable of providing a quite denser measurement over large areas. More specifically, Interferometric SAR (InSAR), Differential InSAR (DInSAR), Persistent Scatterers InSAR (PSI) techniques are developing to meet people¡¯s requirements of detecting land movements. Due to the different features of urban and non-urban area, the application of InSAR for land movements monitoring may come cross different challenges. D¨¹sseldorf was used as the urban test site by processing 20 TerraSAR-X images using PSI. Levelling results provided by the State Capital of D¨¹sseldorf validated the PSInSAR result, when two time series showed similar progress with very few discrepancies. Xishan mining region was chosen as the non-urban test site in this project, because of clear advantages. Such as well served mining schedule and literature and rapid movements with big phase gradients. In the experiments carried out in Xishan mine, InSAR fulfilled the aim of mining parameters derivation. GPS surveying was collated for the coordinates of corner reflectors, which can validate and improve the accuracy of geocoding (better than 5 m).Die Überwachung von Setzungen in städtischen Gebieten wird immer wichtiger, da es sich um eine potenzielle Bedrohung für die Umwelt und den Menschen handelt. Die Untersuchung von Landsenkungen in nicht-städtischen Bereichen sind ebenfalls sehr wichtig. Mit interferometrischen Auswertungen von Synthetic Aperture Radar Messungen (InSAR) ist man in der Lage große Bereiche hochauflösend zu beobachten. SAR Systeme können während des Tages, der Nacht und unter allen Wetterbedingungen arbeiten. Heutzutage gibt es zunehmendes Interesse an der Anwendung von SAR für das Monitoring von Veränderungen der Erdoberfläche. Hierzu wurden speziell die Techniken des Interferometrischen SAR (InSAR), Differential InSAR (DInSAR) und Persistent Scatterers InSAR (PSI) entwickelt. Aufgrund der unterschiedlichen Merkmale von urbanen und nichturbanen Gebieten, kann die Anwendung von InSAR für das Monitoring von Bewegungen unterschiedliche Herausforderungen stellen. Die Stadt Düsseldorf wurde als Testfeld für die Verarbeitung von 20 TerraSAR-X Bilder mit PSI ausgewählt. Die Ergebnisse aus dem Nivellement der Landeshauptstadt Düsseldorf wurden für die Validierung der PSInSAR Ergebnisse genutzt. Zwei Zeitreihen zeigen einen ähnlichen Verlauf mit sehr geringen Abweichungen. Die Bergbauregion Xishan wurde als nichturbanes Testgebiete in diesem Projekt ausgewählt, weil es die Möglichkeit bietet an Informationen über den Bergbau, die Zeitpläne und Literatur zu kommen und es dort schnelle Oberflächenbewegungen mit großen Phasengradienten gibt. Die durchgeführten Experimente im Xishan Gebiet zeigen, dass man mit der InSAR Auswertung auch Bergbauparameter ableiten kann. Für die Koordinatenbestimmung der Corner Reflektoren wurden GPS Messungen durchgeführt, die auch zur Verbesserung der Satellitenbasislinien dienen und die Genauigkeit der Geokodierung (kleiner 5 m) verbessern

Wireless sensor networks for landslide monitoring: application and optimization by visibility analysis on 3D point clouds

Occurring in many geographical, geological and climatic environments, landslides represent a major geological hazard. In landslide prone areas, monitoring devices associated with Early Warning Systems are a cost-effective means to reduce the risk with a low environmental and economic impact, and in some cases, they can be the only solution. In this framework, particular interest has been reserved for Wireless Sensor Networks (WSNs), defined as networks of usually low-size and low-cost devices denoted as nodes, which are integrated with sensors that can gather information through wireless links. In this thesis, data from a new prototypical ground instability monitoring instrument called Wi-GIM (Wireless sensor network for Ground Instability Monitoring) have been analysed. The system consists in a WSN made by nodes able to measure their mutual inter-distances by calculating the time of flight of an Ultra-Wide Band impulse. Therefore, no sensors are implemented in the network, as the same signals used for transmission are also used for ranging. The system has been tested in a controlled outdoor environment and applied for the monitoring of the displacements of an actual landslide, the Roncovetro mudflow in Central Italy, where a parallel monitoring with a Robotic Total Station (RTS) allowed to validate the system. The outputs are displacement time series showing the distance of each couple of nodes belonging to the same cluster. Data retrieved from the tests revealed a precision of 2–5 cm and that measurements are influenced by the temperature. Since the correlation with this parameter has proved to be linear, a simple correction is sufficient to improve the precision and remove the effect of temperature. The campaign also revealed that measurements were not affected by rain or snow, and that the system can efficiently communicate up to 150 m with a 360° angle of view without affecting precision. Other key features of the implemented system are easy and quick installation, flexibility, low cost, real-time monitoring and acquisition frequency changeability. The comparison between Wi-GIM and RTS measurements pointed out the presence of an offset (in an order that vary from centimetric to decametric) constant for each single couple, due mainly to the presence of obstacles that can obstruct the Line Of Sight (LOS). The presence of vegetation is the main cause of the non-LOS condition between two nodes, which translates in a longer path of the signals and therefore to a less accurate distance measurements. To go further inside this issue, several tests have been carried out proving the strong influence of the vegetation over both data quantity and quality. To improve them, a MATLAB tool (R2018a, MAthWorks, Natick, MA, USA) called WiSIO (Wireless Sensor network Installation Optimizer) has been developed. The algorithm finds the best devices deployment following three criteria: (i) inter-visibility by means of a modified version of the Hidden Point Removal operator; (ii) equal distribution; (iii) positioning in preselected priority areas. With respect to the existing viewshed analysis, the main novelty is that it works directly with 3D point clouds, without rendering them or performing any surface. This lead to skip the process of generating surface models avoiding errors and approximations, that is essential when dealing with vegetation. A second installation of the Wi-GIM system has been therefore carried out considering the deployment suggested by WiSIO. The comparison of data acquired by the system positioned with and without the help of the proposed algorithm allowed to better comprehend the effectiveness of the tool. The presented results are very promising, showing how a simple elaboration can be essential to have more and more reliable data, improving the Wi-GIM system performances, making it even more usable in very complex environments and increasing its flexibility. The main left limitation of the Wi-GIM system is currently the precision. Such issue is connected to the aim of using only low-cost components, and it can be prospectively overcome if the system undergoes an industrialization process. Furthermore, since the system architecture is re-adaptable, it is prone to enhancements as soon as the technology advances and new low cost hardware enters the market

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

Characterization of Ground Deformation Associated with Shallow Groundwater Processes Using Satellite Radar Interferometry

Shallow groundwater processes maylead to ground deformation and even geohazards. With the features of day-and-night accessibility and large-scale coverage, time-series interferometric synthetic aperture radar (InSAR) has proven a useful tool for mapping the deformation over various landscapes at cm to mm level with weekly to monthly updates. However, it has limitations such as, decorrelation,atmospheric artifacts, topographic errors, andunwrapping errors, in particular for the hilly, vegetated, and complicated deformation patterns. In this dissertation, I focus on characterizing the ground deformation over landslides, aquifer systems, and mine tailings impoundment, using the designed advanced time-series InSAR strategy, as well as theinterdisciplinary knowledge of geodesy, hydrology, geophysics, and geology. Northwestern USA has been exposed to extreme landslide hazards due to steep terrain, high precipitation, and loose root support after wildfire. I characterize the rainfall-triggered movements of Crescent Lake landslide, Washington State. The seasonal deformation at the lobe, with larger magnitudes than the downslope riverbank, suggests an amplified hydrological loading effect due to a thicker unconsolidated zone. High-temporal-resolution InSAR and GPS data reveal dynamic landslide motions. Threshold rainfall intensities and durations wet seasons have been associated with observed movement upon shearing: antecedent rainfall triggered precursory slope-normal subsidence, and the consequent increase in pore pressure at the basal surface reduces friction and instigates downslope slip over the course of less than one month. In addition, a quasi-three-dimensional deformation field is created using multiple spaceborne InSAR observations constrained by the topographical slope, and is further used to invert for the complex geometry of landslide basal surface based on mass conservation. Aquifer skeletons deform in response to hydraulic head changes with various time scales of delay and sensitivity. I investigate the spatio-temporal correlation among deformation, hydrological records and earthquake records over Salt Lake Valley, Utah State. A clear long-term and seasonal correlation exists between surface uplift/subsidence and groundwater recharge/discharge, allowing me to quantify hydrogeological properties. Long-term uplift reflects the net pore pressure increase associated with prolonged water recharge, probably decades ago. The distributions of previously and newly mapped faults suggest that the faultsdisrupt the groundwater flow andpartition hydrological units. Mine tailings gradual settle as the pore pressure dissipates and the terrain subsides, andtailings embankment failures can be extremely hazardous. I investigate the dynamics of consolidation settlement over the tailings impoundment in the vicinity of Great Salt Lake, Utah State, as well as its associated impacts to the surrounding infrastructures. Largest subsidence has been observed around the low-permeable decant pond clay at the northeast corner.The geotechnical consolidation model reveals and predicts the long-term exponentially decaying settlement process. My studies have demonstrated that InSAR methods can advance our understanding about the potential anthropogenic impacts and natural hydrological modulations on various geodynamic settings in geodetic time scale

Processing of optic and radar images.Application in satellite remote sensing of snow, ice and glaciers

Ce document présente une synthèse de mes activités de recherche depuis la soutenance de ma thèse en 1999. L'activité rapportée ici est celle d'un ingénieur de recherche, et donc s'est déroulée en parallèle d'une activité ``technique'' comprenant des taches d'instrumentation en laboratoire, d'instrumentation de plateformes en montagne, de raids scientifiques sur les calottes polaires, d'élaboration de projets scientifiques, d'organisation d'équipes ou d'ordre administratif. Je suis Ingénieur de recherche CNRS depuis 2004 affecté au laboratoire Gipsa-lab, une unité mixte de recherche du CNRS, de Grenoble-INP, de l'université Joseph Fourier et de l'université Stendhal. Ce laboratoire (d'environ 400 personnes), conventionné avec l'INRIA, l'Observatoire de Grenoble et l'université Pierre Mendès France, est pluridisciplinaire et développe des recherches fondamentales et finalisées sur les signaux et les systèmes complexes.}Lors de la préparation de ma thèse (mi-temps 1995-99) au LGGE, je me suis intéressé au traitement des images de microstructures de la neige, du névé et de la glace. C'est assez naturellement que j'ai rejoint le laboratoire LIS devenu Gipsa-lab pour y développer des activités de traitement des images Radar à Synthèse d'Ouverture (RSO) appliqué aux milieux naturels neige, glace et glaciers. Etant le premier à générer un interférogramme différentiel des glaciers des Alpes, j'ai continué à travailler sur la phase interférométrique pour extraire des informations de déplacement et valider ces méthodes sur le glacier d'Argentière (massif du Mont-Blanc) qui présente l'énorme avantage de se déplacer de quelques centimètres par jour. Ces activités m'ont amené à développer, en collaboration avec les laboratoires LISTIC, LTCI et IETR, des méthodes plus générales pour extraire des informations dans les images RSO.Ma formation initiale en électronique, puis de doctorat en physique m'ont amené à mettre à profit mes connaissances en traitement d'images et des signaux, en électromagnétisme, en calcul numérique, en informatique et en physique de la neige et de la glace pour étudier les problèmes de traitement des images RSO appliqués à la glace, aux glaciers et à la neige

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

Advanced satellite radar interferometry for small-scale surface deformation detection

Synthetic aperture radar interferometry (InSAR) is a technique that enables generation of Digital Elevation Models (DEMs) and detection of surface motion at the centimetre level using radar signals transmitted from a satellite or an aeroplane. Deformation observations can be performed due to the fact that surface motion, caused by natural and human activities, generates a local phase shift in the resultant interferogram. The magnitude of surface deformation can be estimated directly as a fraction of the wavelength of the transmitted signal. Moreover, differential InSAR (DInSAR) eliminates the phase signal caused by relief to yield a differential interferogram in which the signature of surface deformation can be seen. Although InSAR applications are well established, the improvement of the interferometry technique and the quality of its products is highly desirable to further enhance its capabilities. The application of InSAR encounters problems due to noise in the interferometric phase measurement, caused by a number of decorrelation factors. In addition, the interferogram contains biases owing to satellite orbit errors and atmospheric heterogeneity These factors dramatically reduce the stlectiveness of radar interferometry in many applications, and, in particular, compromise detection and analysis of small-scale spatial deformations. The research presented in this thesis aim to apply radar interferometry processing to detect small-scale surface deformations, improve the quality of the interferometry products, determine the minimum and maximum detectable deformation gradient and enhance the analysis of the interferometric phase image. The quality of DEM and displacement maps can be improved by various methods at different processing levels. One of the methods is filtering of the interferometric phase.However, while filtering reduces noise in the interferogram, it does not necessarily enhance or recover the signal. Furthermore, the impact of the filter can significantly change the structure of the interferogram. A new adaptive radar interferogram filter has been developed and is presented herein. The filter is based on a modification to the Goldstein radar interferogram filter making the filter parameter dependent on coherence so that incoherent areas are filtered more than coherent areas. This modification minimises the loss of signal while still reducing the level of noise. A methodology leading to the creation of a functional model for determining minimum and maximum detectable deformation gradient, in terms of the coherence value, has been developed. The sets of representative deformation models have been simulated and the associated phase from these models has been introduced to real SAR data acquired by ERS-1/2 satellites. A number of cases of surface motion with varying magnitudes and spatial extent have been simulated. In each case, the resultant surface deformation has been compared with the 'true' surface deformation as defined by the deformation model. Based on those observations, the functional model has been developed. Finally, the extended analysis of the interferometric phase image using a wavelet approach is presented. The ability of a continuous wavelet transform to reveal the content of the wrapped phase interferogram, such as (i) discontinuities, (ii) extent of the deformation signal, and (iii) the magnitude of the deformation signal is examined. The results presented represent a preliminary study revealing the wavelet method as a promising technique for interferometric phase image analysis