Radar satellite imagery for humanitarian response. Bridging the gap between technology and application

This work deals with radar satellite imagery and its potential to assist of humanitarian operations. As the number of displaced people annually increases, both hosting countries and relief organizations face new challenges which are often related to unclear situations and lack of information on the number and location of people in need, as well as their environments. It was demonstrated in numerous studies that methods of earth observation can deliver this important information for the management of crises, the organization of refugee camps, and the mapping of environmental resources and natural hazards. However, most of these studies make use of -high-resolution optical imagery, while the role of radar satellites is widely neglected. At the same time, radar sensors have characteristics which make them highly suitable for humanitarian response, their potential to capture images through cloud cover and at night in the first place. Consequently, they potentially allow quicker response in cases of emergencies than optical imagery. This work demonstrates the currently unused potential of radar imagery for the assistance of humanitarian operations by case studies which cover the information needs of specific emergency situations. They are thematically grouped into topics related to population, natural hazards and the environment. Furthermore, the case studies address different levels of scientific objectives: The main intention is the development of innovative techniques of digital image processing and geospatial analysis as an answer on the identified existing research gaps. For this reason, novel approaches are presented on the mapping of refugee camps and urban areas, the allocation of biomass and environmental impact assessment. Secondly, existing methods developed for radar imagery are applied, refined, or adapted to specifically demonstrate their benefit in a humanitarian context. This is done for the monitoring of camp growth, the assessment of damages in cities affected by civil war, and the derivation of areas vulnerable to flooding or sea-surface changes. Lastly, to foster the integration of radar images into existing operational workflows of humanitarian data analysis, technically simple and easily-adaptable approaches are suggested for the mapping of rural areas for vaccination campaigns, the identification of changes within and around refugee camps, and the assessment of suitable locations for groundwater drillings. While the studies provide different levels of technical complexity and novelty, they all show that radar imagery can largely contribute to the provision of a variety of information which is required to make solid decisions and to effectively provide help in humanitarian operations. This work furthermore demonstrates that radar images are more than just an alternative image source for areas heavily affected by cloud cover. In fact, what makes them valuable is their information content regarding the characteristics of surfaces, such as shape, orientation, roughness, size, height, moisture, or conductivity. All these give decisive insights about man-made and natural environments in emergency situations and cannot be provided by optical images Finally, the findings of the case studies are put into a larger context, discussing the observed potential and limitations of the presented approaches. The major challenges are summarized which need be addressed to make radar imagery more useful in humanitarian operations in the context of upcoming technical developments. New radar satellites and technological progress in the fields of machine learning and cloud computing will bring new opportunities. At the same time, this work demonstrated the large need for further research, as well as for the collaboration and transfer of knowledge and experiences between scientists, users and relief workers in the field. It is the first extensive scientific compilation of this topic and the first step for a sustainable integration of radar imagery into operational frameworks to assist humanitarian work and to contribute to a more efficient provision of help to those in need.Die vorliegende Arbeit beschäftigt sich mit bildgebenden Radarsatelliten und ihrem potenziellen Beitrag zur Unterstützung humanitärer Einsätze. Die jährlich zunehmende Zahl an vertriebenen oder geflüchteten Menschen stellt sowohl Aufnahmeländer als auch humanitäre Organisationen vor große Herausforderungen, da sie oft mit unübersichtlichen Verhältnissen konfrontiert sind. Effektives Krisenmanagement, die Planung und Versorgung von Flüchtlingslagern, sowie der Schutz der betroffenen Menschen erfordern jedoch verlässliche Angaben über Anzahl und Aufenthaltsort der Geflüchteten und ihrer natürlichen Umwelt. Die Bereitstellung dieser Informationen durch Satellitenbilder wurde bereits in zahlreichen Studien aufgezeigt. Sie beruhen in der Regel auf hochaufgelösten optischen Aufnahmen, während bildgebende Radarsatelliten bisher kaum Anwendung finden. Dabei verfügen gerade Radarsatelliten über Eigenschaften, die hilfreich für humanitäre Einsätze sein können, allen voran ihre Unabhängigkeit von Bewölkung oder Tageslicht. Dadurch ermöglichen sie in Krisenfällen verglichen mit optischen Satelliten eine schnellere Reaktion. Diese Arbeit zeigt das derzeit noch ungenutzte Potenzial von Radardaten zur Unterstützung humanitärer Arbeit anhand von Fallstudien auf, in denen konkrete Informationen für ausgewählte Krisensituationen bereitgestellt werden. Sie sind in die Themenbereiche Bevölkerung, Naturgefahren und Ressourcen aufgeteilt, adressieren jedoch unterschiedliche wissenschaftliche Ansprüche: Der Hauptfokus der Arbeit liegt auf der Entwicklung von innovativen Methoden zur Verarbeitung von Radarbildern und räumlichen Daten als Antwort auf den identifizierten Forschungsbedarf in diesem Gebiet. Dies wird anhand der Kartierung von Flüchtlingslagern zur Abschätzung ihrer Bevölkerung, zur Bestimmung von Biomasse, sowie zur Ermittlung des Umwelteinflusses von Flüchtlingslagern aufgezeigt. Darüber hinaus werden existierende oder erprobte Ansätze für die Anwendung im humanitären Kontext angepasst oder weiterentwickelt. Dies erfolgt im Rahmen von Fallstudien zur Dynamik von Flüchtlingslagern, zur Ermittlung von Schäden an Gebäuden in Kriegsgebieten, sowie zur Erkennung von Risiken durch Überflutung. Zuletzt soll die Integration von Radardaten in bereits existierende Abläufe oder Arbeitsroutinen in der humanitären Hilfe anhand technisch vergleichsweise einfacher Ansätze vorgestellt und angeregt werden. Als Beispiele dienen hier die radargestützte Kartierung von entlegenen Gebieten zur Unterstützung von Impfkampagnen, die Identifizierung von Veränderungen in Flüchtlingslagern, sowie die Auswahl geeigneter Standorte zur Grundwasserentnahme. Obwohl sich die Fallstudien hinsichtlich ihres Innovations- und Komplexitätsgrads unterscheiden, zeigen sie alle den Mehrwert von Radardaten für die Bereitstellung von Informationen, um schnelle und fundierte Planungsentscheidungen zu unterstützen. Darüber hinaus wird in dieser Arbeit deutlich, dass Radardaten für humanitäre Zwecke mehr als nur eine Alternative in stark bewölkten Gebieten sind. Durch ihren Informationsgehalt zur Beschaffenheit von Oberflächen, beispielsweise hinsichtlich ihrer Rauigkeit, Feuchte, Form, Größe oder Höhe, sind sie optischen Daten überlegen und daher für viele Anwendungsbereiche im Kontext humanitärer Arbeit besonders. Die in den Fallstudien gewonnenen Erkenntnisse werden abschließend vor dem Hintergrund von Vor- und Nachteilen von Radardaten, sowie hinsichtlich zukünftiger Entwicklungen und Herausforderungen diskutiert. So versprechen neue Radarsatelliten und technologische Fortschritte im Bereich der Datenverarbeitung großes Potenzial. Gleichzeitig unterstreicht die Arbeit einen großen Bedarf an weiterer Forschung, sowie an Austausch und Zusammenarbeit zwischen Wissenschaftlern, Anwendern und Einsatzkräften vor Ort. Die vorliegende Arbeit ist die erste umfassende Darstellung und wissenschaftliche Aufarbeitung dieses Themenkomplexes. Sie soll als Grundstein für eine langfristige Integration von Radardaten in operationelle Abläufe dienen, um humanitäre Arbeit zu unterstützen und eine wirksame Hilfe für Menschen in Not ermöglichen

Satellite remote sensing and non-destructive testing methods for transport infrastructure monitoring: advances, challenges and perspectives

High temporal frequency monitoring of transport infrastructure is crucial to prioritise mainte-nance and prevent major service disruption or structural failures. Ground-based non-destructive testing (NDT) methods have been successfully applied for decades, reaching very high standards for data quality and accuracy. However, routine campaigns and long inspection times are re-quired for data collection and their implementation into reliable infrastructure management systems (IMSs). On the other hand, satellite remote sensing techniques, such as the Mul-ti-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method, have proven effective in monitoring ground displacements of transport infrastructure (roads, railways and airfields) with a much higher temporal frequency of investigation and the capability to cover wider areas. Nevertheless, the integration of information from i) satellite remote sensing and ii) ground-based NDT methods is still a subject to be fully explored in civil engineering. This paper aims to review significant stand-alone and combined applications in these two areas of endeavour for transport infrastructure monitoring. Recent advances, main challenges and future perspectives arising from their mutual integration are also discussed

From site-scale to large areas monitoring of ground deformation phenomena by integration of different DInSAR techniques in Crotone Province (Southern Italy)

One of the most significant aims of this research project has been to apply SAR methods for the monitoring, the investigation and the evaluation of ground deformation phenomena in the Crotone province (Southern Italy). In detail, landslides and subsidence are the most remarkable and dangerous natural hazards in the study area, affecting people, buildings and main infrastructures. The intention was to show the potential of Differential Interferometry SAR (DInSAR) techniques for the detection and the estimation of the velocities and of the deformation of surface displacements, both on very local scale (slope scale) and on wide areas (kilometre-size extension). Such aim is achievable through the integration of DInSAR techniques along with conventional monitoring tools. The general idea of the project has been to assess the landslide hazard in selected areas of the Crotone province and to update the related landslide inventory map of the area, dated back to 2006, by means of DInSAR techniques. These goals have been reached through the comprehension and the understanding of the movements, on one hand on a very local scale (slope), and on the other hand, on a wide-area scale (the whole Crotone province). Additionally, two other case studies of subsidence, originated by different sources, have been studied with interferometry techniques, showing the suitability of such methods for other types of ground deformation. Several Multi Temporal Interferometry (MTI, Wasowski & Bovenga, 2014) approaches have been here applied, in order to investigate and analyze displacements present in the area, and the integration with “conventional” methods, such as inclinometers, piezometers and geomorphological surveys, turned out to be relevant for these purposes, providing very precise information about the nature and causes of ground deformation

Interferometric Synthetic Aperture Radar for remote satellite monitoring of bridges

The structural health of critical infrastructure is difficult to assess and monitor with existing methods of evaluation which rely predominantly on visual inspection and/or the installation of sensors to measure the in-situ performance of structures. There are vast numbers of critical structures that need to be monitored and these are often located in diverse geographical locations which are difficult and costly to access. Recent advances in satellite technologies provide the opportunity for global coverage of assets and the measurement of displacement to sub-centimetre accuracy. Such measurements could supplement existing monitoring techniques and provide asset owners with additional insights which could inform operational and maintenance decisions. Most past research within the field of Interferometric Synthetic Aperture Radar (InSAR) monitoring using satellite radar imagery focusses on widespread measurement of land areas, although there have been some case studies using InSAR to assess movements of individual structures such as dams. However, there is limited published research into the use of these techniques for accurately monitoring the displacements of individual civil engineering structures over time and relating these measurements to structural performance. This research focusses on bridges as a specific example of critical infrastructure to establish whether remote satellite monitoring can be used to measure displacements at a resolution that is sufficiently accurate for use in monitoring of performance, and examines the relevance and limitations of satellite monitoring to civil engineering applications in general. In order to assess the millimetre-scale performance of InSAR, an initial evaluation was undertaken in controlled conditions on a purpose-built test bed fitted with satellite reflectors at the National Physical Laboratory in Teddington to validate InSAR displacement measurements against traditional terrestrial in-situ displacement measurements. Subsequently, traditional sensor and surveying measurements of displacements were compared with InSAR displacement measurements at key points of interest on Waterloo Bridge and the Hammersmith Flyover. A further case study on Tadcaster Bridge was undertaken to demonstrate the potential applicability of InSAR displacement measuring techniques for monitoring bridges at risk of scour failure. Scour is the most common form of bridge collapse around the world and to date no cost-effective and widely applicable method for providing advanced warning of impending failure due to scour has been developed. Methodologies for integrating digital, structural and signal processing models for the identification and mapping of InSAR measurement points on bridge structures from SAR imagery were developed, as well as methodologies for combining satellite data with traditional surveying methods. An important outcome of this research was that through comparison of independent measurements, InSAR measurements are of a scale that is applicable to bridge monitoring. Remote sensing can therefore reach global coverage, with unsupervised readings over an interval of days, and as such supplement traditional inspection regimes. However, this outcome must be presented with several limitations. Practical implications of applying InSAR to real bridges are discussed, including imaging effects and the suitability of monitoring different forms of bridge deformation. The key to successful implementation of InSAR monitoring of bridges lies in understanding the limitations and opportunities of InSAR, and making a clear case to satellite data providers on what specifications (resolution, frequency, processing assumptions) would unlock using such datasets for wider use in monitoring of infrastructure. InSAR can provide measurements and useful insights for bridge monitoring but it is limited to specific cases and, at this stage of technological development, it should be considered as a tool for specific bridges and failure mechanisms rather than a full bridge monitoring solution.This PhD was funded by the Engineering and Physical Sciences Research Council (EPSRC), U.K., under Award 1636878 with iCASE sponsorship by the National Physical Laboratory. Further funding contributions were provided by Laing O’Rourke. Projects within the PhD received funding from Innovate UK and some of the data was provided by the German Aerospace Centre (DLR) under proposal MTH3513

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

Integrated analysis of building vulnerability in urban areas affected by slow-moving, intermittent landslides using SAR Interferometry

Slow-moving landslides are a natural hazard which affects wide areas in the world causing relevant economic damage to structures and infrastructures. To this reason, the analysis of landslide-induced consequences plays a key role in risk prevention and mitigation activities. The thesis shows a general methodology which can be used to forecast spatial and temporal evolution of building vulnerability in urban settlements affected by slow-moving and intermittent landslides. Multi-level and integrated analysis of landslide kinematics and exposed elements allows to assess at different scales of representation and at different levels of accuracy, future conditions of damage of existing facilities. Satellite Radar Interferometry and in particular the Differential SAR Interferometry (DInSAR) technique has been successfully applied as a remote-sensing tool to provide information both on spatial and temporal landslide evolution and on interaction with structures in urban areas. Integration of C and X-band SAR data (acquired between 2002 and 2016) with conventional monitoring techniques allows to reach a thorough knowledge of landslide kinematics; subsequently, structural analyses to detect the relationship between slope movements and building damage have been performed, by using qualitative, semi-quantitative and quantitative approaches. Such methodology has been tested in Moio della Civitella urban settlement, Salerno Province, whose territory is affected by several slow-moving landslides. At small scale of representation, preliminary cause-effect relationship and the updating of landslide inventory map have been provided; at medium scale of analysis, vulnerability zoning map through matrix-approach and influence of vulnerability factors on performance of structures through fragility curves approach, have been defined. Finally, at a detailed scale, structural behavior of buildings has been investigated by means of analytical or numerical analyses. The proposed methodology could be applied to other scenarios affected by similar phenomena and once validated, can be valuably used for damage analysis and forecasting

Application of Differential and Polarimetric Synthetic Aperture Radar (SAR) Interferometry for Studying Natural Hazards

In the following work, I address the problem of coherence loss in standard Differential Interferometric SAR (DInSAR) processing, which can result in incomplete or poor quality deformation measurements in some areas. I incorporate polarimetric information with DInSAR in a technique called Polarimetric SAR Interferometry (PolInSAR) in order to acquire more accurate and detailed maps of surface deformation. In Chapter 2, I present a standard DInSAR study of the Ahar double earthquakes (Mw=6.4 and 6.2) which occurred in northwest Iran, August 11, 2012. The DInSAR coseismic deformation map was affected by decorrelation noise. Despite this, I employed an advanced inversion technique, in combination with a Coulomb stress analysis, to find the geometry and the slip distribution on the ruptured fault plane. The analysis shows that the two earthquakes most likely occurred on a single fault, not on conjugate fault planes. This further implies that the minor strike-slip faults play more significant role in accommodating convergence stress accumulation in the northwest part of Iran. Chapter 3 presents results from the application of PolInSAR coherence optimization on quad-pol RADARSAT-2 images. The optimized solution results in the identification of a larger number of reliable measurement points, which otherwise are not recognized by the standard DInSAR technique. I further assess the quality of the optimized interferometric phase, which demonstrates an increased phase quality with respect to those phases recovered by applying standard DInSAR alone. Chapter 4 discusses results from the application of PolInSAR coherence optimization from different geometries to the study of creep on the Hayward fault and landslide motions near Berkeley, CA. The results show that the deformation rates resolved by PolInSAR are in agreement with those of standard DInSAR. I also infer that there is potential motion on a secondary fault, northeast and parallel to the Hayward fault, which may be creeping with a lower velocity

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