Monitoring von Hangbewegungen mit InSAR Techniken im Gebiet Ciloto, Indonesien

In this doctoral thesis, the InSAR techniques are applied to detect the ground movement phenomenon and to assess the InSAR result geometrically in the Ciloto area, Indonesia. Mainly, one of those techniques, the SB-SDFP algorithm, overcomes the limitations of conventional InSAR in monitoring rural and agricultural areas and can observe extremely slow landslides. The InSAR strategy is positively known as a promising option to detect and quantify the kinematics of active landslides on a large areal scale. To minimize the bias of the InSAR displacement result, the correction of the tropospheric phase delay was carried out in a first step. This procedure is demonstrated in experiments both in the small study area in Ciloto and in a larger area. The latter is an area located in Northern Baja California, Mexico and is dominated by tectonic activity as well as groundwater-induced subsidence. A detailed investigation of the slope movement's behavior in the Ciloto district was conducted utilizing multi-temporal and multi-band SAR data from ERS1/2 (1996-1999), ALOS PALSAR (2007-2009) and Sentinel-1 (2014-2018) satellites. The region was successfully identified as a permanent active landslide prone area, especially in the vicinity of the Puncak Pass and Puncak Highway. The full 3D velocity field and the displacement time series were estimated using the inversion model. The velocity rate was classified from extremely slow to slow movement. To comprehend the landslide's behavior, a further examination of the relationship between InSAR results and physical characteristics of the area was carried out. For the long period of a slow-moving landslide, the relationship between precipitation and displacement trend shows a weak correlation. It is concluded that the extremely slow to slow deformation is not directly influenced by the rainfall intensity, yet it effectuates the subsurface and the groundwater flow. The run-off process with rainfall exceeding a soil's infiltration capacity was suspected as the main driver of the slow ground movement phenomenon. However, when analyzing rapid and extremely rapid landslide events at Puncak Pass, a significant increase in the correlation coefficient between precipitation and displacement rate could be observed.In dieser Doktorarbeit wird die Anwendung von erweiterten Verarbeitungsstrategien von InSAR Daten zur Erkennung und geometrischen Bewertung der Bodenbewegungen im Ciloto - Indonesien dargestellt. Dieser Ansatz überwindet die Beschränkungen konventioneller SAR-Interferometrie und ermöglicht sowohl ein kontinuierliches Monitoring dieses landwirtschaftich geprägten Gebietes als auch die Erfassung extrem langsamer Hangrutschungen. Um eine Verzerrung der InSAR Deformationsergebnisse zu minimieren, wurde zunächst eine Korrektur der troposphärischen Phase durchgeführt. Diese neuartige Strategie wird sowohl im Forschungsgebiet Ciloto als auch an einem größeren Gebiet demonstriert. Bei letzterem handelt es sich um einen Küstenstreifen im nördlichen Niederkalifornien, Mexiko, welcher durch hohe tektonische Aktivität und grundwasserinduzierte Landsetzungen charakterisiert ist. Die detaillierte Untersuchung des Verhaltens von Hangrutschungen im Ciloto erfolgte durch die Verarbeitung multi-temporaler SAR-Daten unter Nutzung verschiedener Frequenzbänder, darunter ESR1/2 (1996-1999), ALOS PALSAR (2007-2009) und Sentinel-1 (2014-2018) Daten. Die Region konnte erfolgreich als permanent aktives Hangrutschungsgebiet identifiziert werden, wobei der Puncak Pass und der Puncak Highway ein erhöhtes Gefahrenpotential aufweisen. Ein 3D- Geschwindig-keitsfeld der Deformation und die zugehörigen Zeitreihen wurden mit dem Inversionsmodell berechnet. Die Geschwindigkeitsrate wurde als langsam bis extrem langsam klassifiziert. Um das dynamische Verhalten der Hangrutschung zu verstehen wurde, in einer weiteren Untersuchung die Beziehung zwischen dem InSAR-Ergebnis und den physikalischen Begebenheiten im Forschungsgebiet analysiert. Es wird der Schluss gezogen, dass die langsame bis extrem langsame Verformung nicht direkt von der Niederschlagsintensität beeinflusst wird, diese sich aber auf den Untergrund und die Grundwasserströmung auswirkt. Es wird vermutet, dass der Oberflächenablauf, welcher die Infiltrationskapazität des Bodens übersteigt, ausschlaggebend für das Phänomen der langsamen Bodenbewegung ist. Für die schnellen und extrem schnellen Hangrutschungen jedoch konnte eine signifikante Erhöhung des Korrelationskoeffizienten zwischen Niederschlag und Verschiebungsrate bei Untersuchungen der Hangrutschung am Puncak-Pass nachgewiesen werden

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

High-accuracy digital elevation model generation and ship monitoring from synthetic aperture radar images: innovative techniques and experimental results.

In this Thesis several state-of-the-art and innovative techniques for Digital Elevation Model (DEM) generation from Synthetic Aperture Radar (SAR) images are deeply analyzed, with a special focus on the methods which allow the improvement of the accuracy of the DEM product, which is directly related to the geolocation accuracy of geocoded images and is considered as an enabling factor for a large series of civilian and Defence applications. Furthermore, some of the proposed techniques, which are based both on phase and amplitude information, are experimented on real data, i.e. COSMO-SkyMed (CSK) data, assessing the achievable performances compared with the state-of-the-art, and pointing out and quantitatively highlighting the acquisition and processing strategies which would allow to maximize the quality of the results. Moreover, a critical analysis is performed about the main errors affecting the applied techniques, as well as the limitations of the orbital configurations, identifying several complementary techniques which would allow to overcome or mitigate the observed drawbacks. An innovative procedure for on-demand DEM production from CSK SAR data is elaborated and proposed, as well as an auto-validation technique which would enable the validation of the produced DEM also where vertical ground truths are not available. Based on the obtained results and on the consequent critical analysis, several interferometric specifications for new generation SAR satellites are identified. Finally, a literature review is proposed about the main state-of-the-art ship monitoring techniques, considered as one of the main fields of application which takes benefit from SAR data, based on single/multi-platform multi-channel SAR data, with a focus on TanDEM-X (TDX). In particular, in Chapter 1 the main concepts concerning SAR operating principles are introduced and the main characteristics and performances of CSK and TDX satellite systems are described; in Chapter 2 a review is proposed about the state-of-the-art SAR interferometric techniques for DEM generation, analyzing all the relevant processing steps and deepening the study of the main solutions recently proposed in the literature to increase the accuracy of the interferometric processing; in Chapter 3 complementary and innovative techniques respect to the interferometric processing are analyzed to mitigate disadvantages and to improve performances; in Chapter 4 experimental results are presented, obtained in the generation of high accuracy DEM by applying to a dataset of CSK images properly selected state-of-the-art interferometric techniques and innovative methods to improve DEM accuracy, exploring relevant limitations, and pointing out innovative acquisition and processing strategies. In Chapter 5, the basic principles of Ground Moving Target Indication (GMTI) are described, focusing on Displaced Phase Center Antenna (DPCA) and Along-Track Interferometry (ATI) techniques

Joint exploitation of space-borne and ground-based multitemporal InSAR measurements for volcano monitoring: The Stromboli volcano case study

Abstract We present a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) and Multi Temporal (MT) InSAR measurements for investigating the Stromboli volcano (Italy) deformation phenomena. In particular, we focus our analysis on three periods: a) the time interval following the 2014 flank eruption, b) the July–August 2019 eruption and c) the following post-eruptive phase. To do this, we take advantage from an unprecedented set of space-borne and ground-based SAR data collected from April 2015 up to November 2019 along two (one ascending and one descending) Sentinel-1 (S-1) tracks, as well as, in the same period, by two ground-based systems installed along the Sciara del Fuoco northern rim. Such data availability permitted us to first characterize the volcano long-term 3D deformation behavior of the pre-eruptive period (April 2015–June 2019), by jointly inverting the space-borne and ground-based InSAR measurements. Then, the GB-SAR measurements allowed us to investigate the sin-eruptive time span (3rd July 2019 – 30th August 2019) which revealed rapid deformation episodes (e.g. more than 30 mm/h just 2 min before the 3rd July 2019 explosion) associated with the eruptive activity, that cannot be detected with the weekly S-1 temporal sampling. Finally, the S-1 measurements permitted to better constrain the post 2019 eruption deformations (31st August 2019 – 5th November 2019), which are mainly located outside the GB-SAR sensed area. The presented results demonstrate the effectiveness of the joint exploitation of the InSAR measurements obtained through satellite and terrestrial SAR systems, highlighting their strong complementarity to map and interpret the deformation phenomena affecting volcanic areas

Method for landslides detection with semi-automatic procedures: The case in the zone center-east of Cauca department, Colombia

Landslides are a common natural hazard that causes human casualties, but also infrastructure damage and land-use degradation. Therefore, a quantitative assessment of their presence is required by means of detecting and recognizing the potentially unstable areas. This research aims to develop a method supported on semiautomatic methods to detect potential mass movements at a regional scale. Five techniques were studied: Morphometry, SAR interferometry (InSAR), Persistent Scatterer InSAR (PS-InSAR), SAR polarimetry (PolSAR) and NDVI composites of Landsat 5, Landsat 7, and Landsat 8. The case study was chosen within the mid-eastern area of the Cauca state, which is characterised by its mountainous terrain and the presence of slope instabilities, officially registered in the CGS-SIMMA landslide inventory. This inventory revealed that the type `slide' occurred with 77.4% from the entire registries, `fall' with 16.5%, followed by `creeps' with 3%, flows with 2.6%, and `lateral spread' with 0.43%. As a result, we obtained the morphometric variables: slope, CONVI, TWI, landform, which were highly associated with landslides. The effect of a DEM in the processing flow of the InSAR method was similar for the InSAR coherence variable using the DEMs ASTER, PALSAR RTC, Topo-map, and SRTM. Then, a multiInSAR analysis gave displacement velocities in the LOS direction between -10 and 10 mm/year. With the dual-PolSAR analysis (Sentinel-1), VH and VV C-band polarised radar energy emitted median values of backscatters, for landslides, about of -14.5 dB for VH polarisation and -8.5 dB for VV polarisation. Also, L-band fully polarimetric NASA-UAVSAR data allowed to nd the mechanism of dispersion of CGS landslide inventory: 39% for surface scattering, 46.4% for volume dispersion, and 14.6% for double-bounce scattering. The optical remote sensing provided NDVI composites derived from Landsat series between 2012 and 2016, showing that NDVI values between 0.40 and 0.70 had a high correlation to landslides. In summary, we found the highest categories related to landslides by Weight of Evidence method (WofE) for each spaceborne technique applied. Finally, these results were merged to generate the landslide detection model by using the supervised machine learning method of Random Forest. By taking training and test samples, the precision of the detection model was of about 70% for the rotational and translational types.Los deslizamientos son una amenaza natural que causa pérdidas humanas, daños a la infraestructura y degradación del suelo. Una evaluación cuantitativa de su presencia se requiere mediante la detección y el reconocimiento de potenciales áreas inestables. Esta investigación tuvo como alcance desarrollar un método soportado en métodos semi-automáticos para detectar potenciales movimientos en masa a escala regional. Cinco técnicas fueron estudiadas: Morfometría, Interferometría radar, Interferometría con Persistent Scatterers, Polarimetría radar y composiciones del NDVI con los satélites Landsat 5, Landsat 7 y Landsat 8. El caso de estudio se seleccionó dentro de la región intermedia al este del departamento del Cauca, la cual se caracteriza por terreno montañoso y la presencia de inestabilidades de la pendiente oficialmente registrados en el servicio SIMMA del Servicio Geológico Colombiano. Este inventario reveló que el tipo de movimiento deslizamiento ocurrió con una frecuencia relativa de 77.4%, caidos con el 16.5% de los casos y reptaciones con 3%, flujos con 2.6% y propagación lateral con 0.43%. Como resultado, se obtuvo las variables morfométricas: pendiente, convergencia, índice topográfico de humedad y forma del terreno altamente asociados con los deslizamientos. El efecto de un DEM en el procesamiento del método InSAR fue similar para la variable coherencia usando los DEMs: ASTER, PAlSAR RTC, Topo-map y SRTM. Un análisis Multi-InSAR estimó velocidades de desplazamiento en dirección de vista del radar entre -10 y 10 mm/año. El análisis de polarimetría dual del Sentinel-1 arrojó valores de retrodispersión promedio de -14.5 dB en la banda VH y -8.5dB en la banda VV. Las cuatro polarimetrías del sensor aéreo UAVSAR permitió caracterizar el mecanismo de dispersión del Inventario de Deslizamiento así: 39% en el mecanismo de superficie, 46.4% en el mecanismo de volumen y 14.6% en el mecanismo de doble rebote. La información generada en el rango óptico permitió obtener composiciones de NDVI derivados de la plataforma Landsat entre los años 2012 y 2016, mostrando que el rango entre 0.4 y 0.7 tuvieron una alta asociación con los deslizamientos. En esta investigación se determinaron las categorías de las variables de Teledetección más altamente relacionadas con los movimientos en masa mediante el método de Pesos de Evidencias (WofE). Finalmente, estos resultados se fusionaron para generar el modelo de detección de deslizamientos usando el método supervisado de aprendizaje de máquina Random Forest. Tomando muestras aleatorias para entrenar y validar el modelo en una proporción 70:30, el modelo de detección, especialmente los movimientos de tipo rotacional y traslacional fueron clasificados con una tasa general de éxito del 70%.Ministerio de CienciasConvocatoria 647 de 2014Research line: Geotechnics and Geoenvironmental HazardDoctorad

Multi-source Satellite Remote Sensing Techniques for Landslide Monitoring and Characterization

Landslides are natural geological hazards that pose significant threats, resulting in economic losses and casualties worldwide. Effective monitoring and characterization of landslides are crucial for understanding their evolution mechanisms and preventing catastrophic failures. While conventional field surveying methods provide accurate measurements of surface deformation, they are limited by high costs in terms of labor and time and uncertainties of arrangement for the ground-based equipment. The Satellite Interferometric Synthetic Aperture Radar (InSAR) technique has proven its application in landslide monitoring, offering advantages such as all-weather operations, wide spatial coverage, high spatial resolution, and high accuracy. InSAR can measure subtle changes along the SAR line-of-sight (LOS) direction but is not sensitive to movements along the north-south direction. Additionally, rapid movements during the failure stage can cause high decorrelation. On the other hand, satellite optical remote sensing data, combined with pixel offset tracking (POT) techniques, can measure large displacements in the horizontal plane. Moreover, multi-spectral analysis of optical images can offer insights into the spatial evolution of landslides. Therefore, the joint use of satellite InSAR and optical remote sensing techniques is complementary in landslide monitoring and characterization. However, the joint utilization of these techniques for capturing the long-term evolutions of landslides, particularly at their different stages using multi-source data, remains relatively unexplored. This dissertation aims to optimize and demonstrate the approaches for the joint use of satellite SAR and optical data in landslide monitoring and characterization across three distinct stages: pre-failure, failure, and post-failure. Three major landslides were studied in this dissertation. Firstly, the surface deformation of the 2017 Maoxian landslide during the pre-failure stage was captured using time series InSAR, while pre-failure slope features were detected from optical images. Secondly, the joint utilization of time series InSAR observations and optical analysis facilitated the monitoring of the pre-failure, failure, and post-failure stages of the 2020 Aniangzhai landslide. Lastly, the long-term post-failure deformation of the Huangtupo landslide in the Three Gorges Reservoir region was mapped using multi-source satellite SAR data, while the multi-temporal optical images were employed to investigate the long-term evolution of surface covers over the slope

Monitoring Snow Cover and Snowmelt Dynamics and Assessing their Influences on Inland Water Resources

Snow is one of the most vital cryospheric components owing to its wide coverage as well as its unique physical characteristics. It not only affects the balance of numerous natural systems but also influences various socio-economic activities of human beings. Notably, the importance of snowmelt water to global water resources is outstanding, as millions of populations rely on snowmelt water for daily consumption and agricultural use. Nevertheless, due to the unprecedented temperature rise resulting from the deterioration of climate change, global snow cover extent (SCE) has been shrinking significantly, which endangers the sustainability and availability of inland water resources. Therefore, in order to understand cryo-hydrosphere interactions under a warming climate, (1) monitoring SCE dynamics and snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced waterbodies, and (3) assessing the causal effect of snowmelt conditions on inland water resources are indispensable. However, for each point, there exist many research questions that need to be answered. Consequently, in this thesis, five objectives are proposed accordingly. Objective 1: Reviewing the characteristics of SAR and its interactions with snow, and exploring the trends, difficulties, and opportunities of existing SAR-based SCE mapping studies; Objective 2: Proposing a novel total and wet SCE mapping strategy based on freely accessible SAR imagery with all land cover classes applicability and global transferability; Objective 3: Enhancing total SCE mapping accuracy by fusing SAR- and multi-spectral sensor-based information, and providing total SCE mapping reliability map information; Objective 4: Proposing a cloud-free and illumination-independent inland waterbody dynamics tracking strategy using freely accessible datasets and services; Objective 5: Assessing the influence of snowmelt conditions on inland water resources

The BIOMASS level 2 prototype processor : design and experimental results of above-ground biomass estimation

BIOMASS is ESA’s seventh Earth Explorer mission, scheduled for launch in 2022. The satellite will be the first P-band SAR sensor in space and will be operated in fully polarimetric interferometric and tomographic modes. The mission aim is to map forest above-ground biomass (AGB), forest height (FH) and severe forest disturbance (FD) globally with a particular focus on tropical forests. This paper presents the algorithms developed to estimate these biophysical parameters from the BIOMASS level 1 SAR measurements and their implementation in the BIOMASS level 2 prototype processor with a focus on the AGB product. The AGB product retrieval uses a physically-based inversion model, using ground-canceled level 1 data as input. The FH product retrieval applies a classical PolInSAR inversion, based on the Random Volume over Ground Model (RVOG). The FD product will provide an indication of where significant changes occurred within the forest, based on the statistical properties of SAR data. We test the AGB retrieval using modified airborne P-Band data from the AfriSAR and TropiSAR campaigns together with reference data from LiDAR-based AGB maps and plot-based ground measurements. For AGB estimation based on data from a single heading, comparison with reference data yields relative Root Mean Square Difference (RMSD) values mostly between 20% and 30%. Combining different headings in the estimation process significantly improves the AGB retrieval to slightly less than 20%. The experimental results indicate that the implemented retrieval scheme provides robust results that are within mission requirements

Radar Interferometry for Monitoring Crustal Deformation. Geodetic Applications in Greece

The chapatti and breadmaking quality of nine (eight Indian and one Australian) wheat (Triticum aestivum L.) cultivars was compared. The extension of a chapatti strip measured with a Kieffer dough extensibility rig correlated with chapatti scores for overall quality (r = 0.84), pliability (r = 0.91), hand feel (r = 0.72), chapatti eating quality (r = 0.68), and taste (r = 0.80). Overall chapatti quality also correlated with the resistance to extension of a chapatti strip (r = 0.68) when tested for uniaxial extension with a texture analyzer. The texture analyzer provided objectivity in the scoring of chapatti quality. The high-molecular-weight glutenin subunit protein composition assessed by sodium dodecyl sulfate polyacrylamide gel electrophoresis did not correlate with the overall chapatti score. A negative correlation was found between chapatti and bread scores (r = 0.77). The different requirements for chapatti and bread quality complicate the breeding of new wheat varieties and the exchange of germplasm between regions producing wheat for chapatti and those supplying bread producers