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

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

Spaceborne InSAR for dam stability

PhD ThesisThis study evaluates the feasibility of the use of satellite radar for dam deformation monitoring. Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has long been used to monitor geohazards, including earthquakes, landslides, and volcanos. However, few studies have recently investigated its feasibility for localised deformation monitoring such as of earth dams. Here two case studies are presented of the monitoring of dams in Iraq. Mosul dam is one of the most dangerous dams in the world. Previous studies have reported that over a million human lives would be potentially at risk should dam failure occur. Therefore, investigation of its health using precise and continuous observations is crucial. This was achieved with two independent geodetic datasets from levelling and InSAR, and the results show continuous vertical displacements on the dam crest due to the dissolution of foundations. Vertical displacement rate estimates from levelling and InSAR for the period 2003-2010 are in good agreement, with a correlation of 0.93 and an RMSE of ± 1.7 mm. For the period 2014- 2017, the correlation is 0.95 and the RMSE is ± 0.9 mm. The movement of the dam was evaluated using settlement index which is not referring to critical instability of the dam. However, the spatial and temporal displacement anomalies emphasize that a careful monitoring and remedial work should continue. The continuous displacement in the dam foundation could loosen the compaction of the embankment and result in internal erosion. In a separate study, Darbandikhan dam was monitored using a global positioning system (GPS), levelling, and Sentinel-1 data to evaluate its stability after the 2017 Mw 7.3 Sarpol-e Zahab earthquake. The large gradient of the dam’s displacements on its crest hindered the estimation of co-seismic displacements using medium-resolution SAR data. However, Sentinel-1 images were sufficient to examine the dam’s stability before and after the earthquake. The results show that the dam was stable between October 2014 and November 2017, but after the earthquake continuous subsidence on the dam crest occurred between November 2017 and March 2018. For the first time the stability of the Mosul and Darbandikhan dams has been assessed using an integration of InSAR and in-situ observations. Different types of deformations were recognized, which helped in interpreting the dam’s deformation mechanismsMinistry of Higher Education (MOHE) and the State Commission of Surveys (SCOS) in Ira

Changement de masse des glaciers à l’échelle mondiale par analyse spatiotemporelle de modèles numériques de terrain

Les glaciers de la planète rétrécissent rapidement, et produisent des impacts qui s'étendent de la hausse du niveau de la mer et la modification des risques cryosphériques jusqu'au changement de disponibilité en eau douce. Malgré des avancées significatives durant l'ère satellitaire, l'observation des changements de masse des glaciers est encore entravée par une couverture partielle des estimations de télédétection, et par une faible contrainte sur les erreurs des évaluations associées. Dans cette thèse, nous présentons une estimation mondiale et résolue des changements de masse des glaciers basée sur l'analyse spatio-temporelle de modèles numériques de terrain. Nous développons d'abord des méthodes de statistiques spatio-temporelles pour évaluer l'exactitude et la précision des modèles numériques de terrain, et pour estimer des séries temporelles de l'altitude de surface des glaciers. En particulier, nous introduisons un cadre spatial non stationnaire pour estimer et propager des corrélations spatiales multi-échelles dans les incertitudes d'estimations géospatiales. Nous générons ensuite des modèles numériques de terrain massivement à partir de deux décennies d'archives d'images optiques stéréo couvrant les glaciers du monde entier. À partir de ceux-ci, nous estimons des séries temporelles d'altitude de surface pour tous les glaciers de la Terre à une résolution de 100,m sur la période 2000--2019. En intégrant ces séries temporelles en changements de volume et de masse, nous révélons une accélération significative de la perte de masse des glaciers à l'échelle mondiale, ainsi que des réponses régionalement distinctes qui reflètent des changements décennaux de conditions climatiques. En utilisant une grande quantité de données indépendantes et de haute précision, nous démontrons la validité de notre analyse pour produire des incertitudes robustes et cohérentes à différentes échelles de la structure spatio-temporelle de nos estimations. Nous espérons que nos méthodes favorisent des analyses spatio-temporelles robustes, en particulier pour identifier les sources de biais et d'incertitudes dans les études géospatiales. En outre, nous nous attendons à ce que nos estimations permettent de mieux comprendre les facteurs qui régissent le changement des glaciers et d'étendre nos capacités de prévision de ces changements à toutes échelles. Ces prédictions sont nécessaires à la conception de politiques adaptatives sur l'atténuation des impacts de la cryosphère dans le contexte du changement climatique.The world's glaciers are shrinking rapidly, with impacts ranging from global sea-level rise and changes in freshwater availability to the alteration of cryospheric hazards. Despite significant advances during the satellite era, the monitoring of the mass changes of glaciers is still hampered by a fragmented coverage of remote sensing estimations and a poor constraint of the errors in related assessments. In this thesis, we present a globally complete and resolved estimate of glacier mass changes by spatiotemporal analysis of digital elevation models. We first develop methods based on spatiotemporal statistics to assess the accuracy and precision of digital elevation models, and to estimate time series of glacier surface elevation. In particular, we introduce a non-stationary spatial framework to estimate and propagate multi-scale spatial correlations in uncertainties of geospatial estimates. We then massively generate digital elevation models from two decades of stereo optical archives covering glaciers worldwide. From those, we estimate time series of surface elevation for all of Earth's glaciers at a resolution of 100,m during 2000--2019. Integrating these time series into volume and mass changes, we identify a significant acceleration of global glacier mass loss, as well as regionally-contrasted responses that mirror decadal changes in climatic conditions. Using a large amount of independent, high-precision data, we demonstrate the validity of our analysis to yield robust and consistent uncertainties at different scales of the spatiotemporal structure of our estimates. We expect our methods to foster robust spatiotemporal analyses, in particular to identify sources of biases and uncertainties in geospatial assessments. Furthermore, we anticipate our estimates to advance the understanding of the drivers that govern glacier change, and to extend our capabilities of predicting these changes at all scales. Such predictions are critically needed to design adaptive policies on the mitigation of cryospheric impacts in the context of climate change

Land Surface Monitoring Based on Satellite Imagery

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 fires and drought

Überwachung von Gasemissionen aktiver Vulkane: Identifizierung von natürlichen Entgasungsvariationen und Kombination von Vulkanüberwachungstechniken

This thesis is a contribution to the interdisciplinary field of applied volcanology and focuses on the study of volcanic gas emissions by means of ground-based spectroscopic remote sensing techniques. Furthermore it aims at fostering the routine use and integration of such measurements into existing multi-parameter volcano surveillance networks of the involved local volcano observatories. For this purpose continuous long-term monitoring of sulphur dioxide (SO2) emission rates was performed using permanent networks of fully-automated scanning ultraviolet (UV) spectrometers at some of the most active and persistently degassing stratovolcanoes in the volcanic arcs of Chile, Costa Rica and Nicaragua. These measurements yielded detailed time series of SO2 emission rates, which were calculated using differential optical absorption spectroscopy (DOAS) in conjunction with wind transport directions and velocities derived from weather hindcasts of the Global Forecast System (GFS), and delivered insights into the degassing behaviour of the monitored volcanoes.Diese Dissertation ist ein Beitrag zum weitläufigen interdisziplinären Feld der angewandten Vulkanologie und der Studie von vulkanischen Gasemissionen unter der Verwendung von bodengebundenen spektroskopischen Fernerkundungstechniken. Desweiteren zielt sie darauf ab, die routinierte Benutzung und die Integrierung solcher Messungen in die bereits existierenden Multi-Parameter Vulkanüberwachungsnetzwerke der involvierten Vulkanobservatorien zu fördern. Für diese Zwecke wurde an einigen der aktivsten und dauerhaft entgasenden Stratovulkane in Chile, Costa Rica und Nicaragua eine kontinuierliche Langzeitüberwachung von Schwefeldioxid (SO2) -Emissionsraten mittels permanent installierter Netzwerke aus voll-automatischen ultraviolett (UV) –Spektrometer Stationen mit eingebauter Abtastvorrichtung durchgeführt. Diese Messungen lieferten detaillierte Zeitreihen von SO2 –Emissionsraten, die mittels differentieller optischer Absorptionsspektroskopie (DOAS) in Verbindung mit Windrichtungen und Windgeschwindigkeiten aus Rückberechnungen des Global Forecast Systems (GFS) berechnet wurden, und gaben somit Einblicke in das Entgasungsverhalten der überwachten Vulkane und ermöglichten darüber hinaus die gemeinsame Analyse mit komplementären seismischen Überwachungsdaten

Monitoring gas emissions of active volcanoes: Identification of natural degassing variations and combination of volcano monitoring techniques

This thesis is a contribution to the interdisciplinary field of applied volcanology and focuses on the study of volcanic gas emissions by means of ground-based spectroscopic remote sensing techniques. Furthermore it aims at fostering the routine use and integration of such measurements into existing multi-parameter volcano surveillance networks of the involved local volcano observatories. For this purpose continuous long-term monitoring of sulphur dioxide (SO2) emission rates was performed using permanent networks of fully-automated scanning ultraviolet (UV) spectrometers at some of the most active and persistently degassing stratovolcanoes in the volcanic arcs of Chile, Costa Rica and Nicaragua. These measurements yielded detailed time series of SO2 emission rates, which were calculated using differential optical absorption spectroscopy (DOAS) in conjunction with wind transport directions and velocities derived from weather hindcasts of the Global Forecast System (GFS), and delivered insights into the degassing behaviour of the monitored volcanoes

Using a new generation of remote sensing to monitor Peru’s mountain glaciers

Remote sensing technologies are integral to monitoring mountain glaciers in a warming world. Tropical glaciers, of which around 70% are located in Peru, are particularly at risk as a result of climate warming. Satellite missions and field-based platforms have transformed understanding of the processes driving mountain glacier dynamics and the associated emergence of hazards (e.g. avalanches, floods, landslides), yet are seldom specialised to overcome the unique challenges of acquiring data in mountainous environments. A ‘new generation’ of remote sensing, marked by open access to powerful cloud computing and large datasets, high resolution satellite missions, and low-cost science-grade field sensors, looks to revolutionise the way we monitor the mountain cryosphere. In this thesis, three novel remote sensing techniques and their applicability towards monitoring the glaciers of the Peruvian Cordillera Vilcanota are examined. Using novel processing chains and image archives generated by the ASTER satellite, the first mass balance estimate of the Cordillera Vilcanota is calculated (-0.48 ± 0.07 m w.e. yr-1) and ELA change of up to 32.8 m per decade in the neighbouring Cordillera Vilcabamba is quantified. The performance of new satellite altimetry missions, Sentinel-3 and ICESat-2, are assessed, with the tracking mode of Sentinel-3 being a key limitation of the potential for its use over mountain environments. Although currently limited in its ability to extract widespread mass balance measurements over mountain glaciers, other applications for ICESat-2 in long-term monitoring of mountain glaciers include quantifying surface elevation change, identifying large accumulation events, and monitoring lake bathymetry. Finally, a novel low-cost method of performing timelapse photogrammetry using Raspberry Pi camera sensors is created and compared to 3D models generated by a UAV. Mean difference between the Raspberry Pi and UAV sensors is 0.31 ± 0.74 m, giving promise to the use of these sensors for long-term monitoring of recession and short-term warning of hazards at glacier calving fronts. Together, this ‘new generation’ of remote sensing looks to provide new glaciological insights and opportunities for regular monitoring of data-scarce mountainous regions. The techniques discussed in this thesis could benefit communities and societal programmes in rapidly deglaciating environments, including across the Cordillera Vilcanota

Monitoring wetlands and water bodies in semi-arid Sub-Saharan regions

Surface water in wetlands is a critical resource in semi-arid West-African regions that are frequently exposed to droughts. Wetlands are of utmost importance for the population as well as the environment, and are subject to rapidly changing seasonal fluctuations. Dynamics of wetlands in the study area are still poorly understood, and the potential of remote sensing-derived information as a large-scale, multi-temporal, comparable and independent measurement source is not exploited. This work shows successful wetland monitoring with remote sensing in savannah and Sahel regions in Burkina Faso, focusing on the main study site Lac Bam (Lake Bam). Long-term optical time series from MODIS with medium spatial resolution (MR), and short-term synthetic aperture radar (SAR) time series from TerraSAR-X and RADARSAT-2 with high spatial resolution (HR) successfully demonstrate the classification and dynamic monitoring of relevant wetland features, e.g. open water, flooded vegetation and irrigated cultivation. Methodological highlights are time series analysis, e.g. spatio-temporal dynamics or multitemporal-classification, as well as polarimetric SAR (polSAR) processing, i.e. the Kennaugh elements, enabling physical interpretation of SAR scattering mechanisms for dual-polarized data. A multi-sensor and multi-frequency SAR data combination provides added value, and reveals that dual-co-pol SAR data is most recommended for monitoring wetlands of this type. The interpretation of environmental or man-made processes such as water areas spreading out further but retreating or evaporating faster, co-occurrence of droughts with surface water and vegetation anomalies, expansion of irrigated agriculture or new dam building, can be detected with MR optical and HR SAR time series. To capture long-term impacts of water extraction, sedimentation and climate change on wetlands, remote sensing solutions are available, and would have great potential to contribute to water management in Africa