A Priori Knowledge-Based Post-Doppler STAP for Traffic Monitoring with Airborne Radar

Die Verkehrsüberwachung gewinnt aufgrund des weltweiten Anstiegs der Verkehrsteilnehmer immer mehr an Bedeutung. Sicherer und effizierter Straßenverkehr erfordert detaillierte Verkehrsinformationen. Häufig sind diese lediglich stationär, räumlich stark begrenzt und meist nur auf Hauptverkehrsstraßen verfügbar. In dieser Hinsicht ist ein Ausfall des Telekommunikationsnetzes, beispielsweise im Falle einer Katastrophe, und der damit einhergehende Informationsverlust als kritisch einzustufen. Flugzeuggetragene Radarsysteme mit synthetischer Apertur (eng. Synthetic Aperture Radar - SAR) können für dieses Szenario eine Lösung darstellen, da sie großflächig hochauflösende Bilder generieren können, unabhängig von Tageslicht und Witterungsbedingungen. Sie ermöglichen aufgrund dieser Charakteristik die Detektion von Bewegtzielen am Boden (eng. ground moving target indication – GMTI). Moderne GMTI-Algorithmen und -Systeme, die prinzipiell für die Verkehrsüberwachung verwendbar sind, wurden in der Literatur bereits diskutiert. Allerdings ist die Robustheit dieser Systeme oft mit hohen Kosten, hoher Hardwarekomplexität und hohem Rechenaufwand verbunden. Diese Dissertation stellt einen neuartigen GMTI-Prozessor vor, der auf dem Radar-Mehrkanalverfahren post-Doppler space-time adaptive processing (PD STAP) basiert. Durch die Überlagerung einer Straßenkarte mit einem digitalen Höhenmodell ist es mithilfe des PD STAP möglich, Falschdetektionen zu erkennen und auszuschließen sowie die detektierten Fahrzeuge ihren korrekten Straßenpositionen zu zuordnen. Die präzisen Schätzungen von Position, Geschwindigkeit und Bewegungsrichtung der Fahrzeuge können mit vergleichsweise geringerer Hardware-Komplexität zu niedrigeren Kosten durchgeführt werden. Ferner wird im Rahmen dieser Arbeit ein effizienter Datenkalibrierungsalgorithmus erläutert, der das Ungleichgewicht zwischen den Empfangskanälen sowie die Variation des Dopplerschwerpunkts über Entfernung und Azimut korrigiert und so das Messergebnis verbessert. Darüber hinaus werden neue und automatisierte Strategien zur Erhebung von Trainingsdaten vorgestellt, die für die Schätzung der Clutter-Kovarianzmatrix wegen ihres direkten Einflusses auf die Clutter-Unterdrückung und Zieldetektion essentiell für PD STAP sind. Der neuartige PD STAP Prozessor verfügt über drei verschiedene Betriebsarten, die für militärische und zivile Anwendungen geeignet sind, darunter ein schneller Verarbeitungsalgorithmus der das Potential für eine zukünftige Echtzeit-Verkehrsüberwachung hat. Alle Betriebsarten wurden erfolgreich mit Radar-Mehrkanaldaten des flugzeuggetragenen F-SAR-Radarsensors des DLR getestet

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Ground moving target indication with synthetic aperture radars for maritime surveillance

The explosive growth of shipping traffic all over the World, with around three quarters of the total trade goods and crude oil transported by sea, has raised newly emerging concerns (economical, ecological, social and geopolitical). Geo-information (location and speed) of ocean-going vessels is crucial in the maritime framework, playing a key role in the related environmental monitoring, fisheries management and maritime/coastal security. In this scenario space-based synthetic aperture radar (SAR) remote sensing is a potential tool for globally monitoring the oceans and seas, providing two-dimensional high-resolution imaging capabilities in all-day and all-weather conditions. The combination of ground moving target indication (GMTI) modes with multichannel spaceborne SAR systems represents a powerful apparatus for surveillance of maritime activities. The level of readiness of such a technology for road traffic monitoring is still low, and for the marine scenario is even less mature. Some of the current space-based SAR missions include an experimental GMTI mode with reduced detection capabilities, especially for small and slow moving targets. In this framework, this doctoral dissertation focuses on the study and analysis of the GMTI limitations of current state-of-the-art SAR missions when operating over maritime scenarios and the proposal of novel and optimal multichannel SAR-GMTI architectures, providing subclutter visibility of small (reduced reflectivity) slow moving vessels. This doctoral activity carries out a transversal analysis embracing system-architecture proposal and optimization, processing strategies assessment, performance evaluation, sea/ocean clutter characterization and adequate calibration methodologies suggestion. Firstly, the scarce availability of multichannel SAR-GMTI raw data and the related restrictions to access it have raised the need to implement flexible simulation tools for SAR-GMTI performance evaluation and mission. These simulation tools allow the comparative study and evaluation of the SAR-GMTI mode operated with current SAR missions, showing the reduced ability of these missions to detect small and slow boats in subclutter visibility. Improved performance is achieved with the new multichannel architecture based on non-uniformly distributed receivers (with external deployable antennas), setting the ground for future SAR-GMTI mission development. Some experimental multichannel SAR-GMTI data sets over the sea and acquired with two instruments, airborne F-SAR and spaceborne TerraSAR-X (TSX) platforms, have been processed to evaluate their detection capabilities as well as the adequate processing strategies (including channel balancing). This doctoral activity presents also a preliminary characterization of the sea clutter returns imaged by the spaceborne TSX instrument in a three-level basis, i.e., radiometric, statistical and polarimetric descriptions using experimental polarimetric data. This study has shown that the system-dependent limitations, such as thermal noise and temporal decorrelation, play a key role in the appropriate interpretation of the data and so should be properly included in the physical backscattering models of the sea. Current and most of the upcoming SAR missions are based on active phase array antennas (APAA) technology for the operation of multiple modes of acquisitions. The related calibration is a complex procedure due to the high number of different beams to be operated. Alternative internal calibration methodologies have been proposed and analyzed in the frame of this doctoral thesis. These approaches improved the radiometric calibration performance compared to the conventional ones. The presented formulation of the system errors as well as the proposed alternative strategies set the path to extrapolate the analysis for multichannel SAR systems.L'increment continu del tràfic marítim arreu del món, amb gairebé tres quartes parts del total de mercaderies i cru transportats per mar, porta associats uns impactes canviants a nivell econòmic, ambiental, social i geopolític. La geo-informació (localització i velocitat) dels vaixells té un paper fonamental en el monitoratge ambiental, la gestió de la pesca i la seguretat marítima/costanera. Els radars d'obertura sintètica (SAR, sigles en anglès) embarcats en satèl·lits són una eina molt potent per al monitoratge global dels oceans i dels mars, gràcies a la seva capacitat de generar imatges d'alta resolució amb independència de les condicions meteorològiques i de la llum solar. La detecció de blancs mòbils terrestres (GMTI, sigles en anglès) combinada amb sistemes multicanal SAR és fonamental per a la vigilància de les activitats marítimes. El nivell de maduresa d'aquesta tecnologia per monitorar tràfic rodat és baix, però per al cas marítim encara ho és més. Algunes missions SAR orbitals inclouen el mode GMTI, però amb unes capacitats de detecció reduïdes, especialment per a blancs petits i lents. En aquest marc, la tesi doctoral es centra en l'estudi i anàlisi de les limitacions GMTI dels actuals sistemes SAR operant en entorns marítims, proposant noves configuracions SAR-GMTI multicanal optimitzades per a la detecció de vaixells petits (emmascarats pels retrons radar del mar) i que es mouen lentament. La present dissertació doctoral du a terme un estudi transversal que abasta des de la proposta i optimització de sistemes/configuracions, passant per l'avaluació de les tècniques de processat, fins a l'estudi del rendiment de la missió, caracterització del mar i la valoració de noves metodologies de calibratge. En primer terme, diverses eines de simulació flexibles s'han implementat per poder avaluar les capacitats GMTI de diferents missions tenint en compte la poca disponibilitat de dades multicanal SAR-GMTI. Aquests simuladors permeten l'estudi comparatiu de les capacitats GMTI de les missions SAR orbitals actuals, demostrant les seves reduïdes opcions per identificar vaixells emmascarats pels retorns del mar. En el marc de l'activitat de recerca s'han processat dades experimentals SAR-GMTI multicanal de sistemes aeris (F-SAR) i orbitals (TerraSAR-X), per tal d'avaluar les seves capacitats de detecció de blancs mòbils sobre entorns marítims, proposant les estratègies de processat i calibratge més adients. Com a part de l'activitat de recerca doctoral, s'ha portat a terme una caracterització preliminar dels retorns radar del mar adquirits amb el sensor orbital TerraSAR-X, amb tres nivells d'anàlisi (radiomètric, estadístic i polarimètric). Aquest estudi demostra que aspectes com el soroll tèrmic i la decorrelació temporal, dependents del propi sensor i de l'entorn dinàmic del mar, poden limitar la correcta interpretació de les dades, i per tant, s'han d'incloure en els models físics dels mecanismes de dispersió del mar. Les missions SAR tant actuals com futures es basen en l'explotació de la tecnologia de les agrupacions d'antenes de fase activa (APAA) per operar diferents modes d'adquisició. El procés de calibratge associat és molt complex atès el gran nombre de feixos que es poden utilitzar. En el marc de la tesi doctoral s'han proposat i avaluat metodologies alternatives de calibratge intern per aquests sistemes, amb un millor rendiment en comparació amb les tècniques convencionals. Aquestes estratègies de calibratge, juntament amb la corresponent formulació dels errors de sistema, estableixen les bases per a l'estudi i avaluació en sistemes multicanal SA

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

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

The University Defence Research Collaboration In Signal Processing

This chapter describes the development of algorithms for automatic detection of anomalies from multi-dimensional, undersampled and incomplete datasets. The challenge in this work is to identify and classify behaviours as normal or abnormal, safe or threatening, from an irregular and often heterogeneous sensor network. Many defence and civilian applications can be modelled as complex networks of interconnected nodes with unknown or uncertain spatio-temporal relations. The behavior of such heterogeneous networks can exhibit dynamic properties, reflecting evolution in both network structure (new nodes appearing and existing nodes disappearing), as well as inter-node relations. The UDRC work has addressed not only the detection of anomalies, but also the identification of their nature and their statistical characteristics. Normal patterns and changes in behavior have been incorporated to provide an acceptable balance between true positive rate, false positive rate, performance and computational cost. Data quality measures have been used to ensure the models of normality are not corrupted by unreliable and ambiguous data. The context for the activity of each node in complex networks offers an even more efficient anomaly detection mechanism. This has allowed the development of efficient approaches which not only detect anomalies but which also go on to classify their behaviour

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

Performance factors for airborne short-dwell squinted radar sensors

Millimetre-wave radar in a missile seeker for the engagement of ground targets allows all-weather, day and night, surface imaging and has the ability to detect, classify and geolocate objects at long ranges. The use of a seeker allows intelligent target selection and removes inaccuracies in the target position. The selection of the correct target against a cluttered background in radar imagery is a challenging problem, which is further constrained by the seeker’s hardware and flight-path. This thesis examines how to make better use of the components of radar imagery that support target selection. Image formation for a squinted radar seeker is described, followed by an approach to automatic target recognition. Size and shape information is considered using a model-matching approach that is not reliant on extensive databases of templates, but a limited set of shape-only templates to reject clutter objects. The effects of radar sensitivity on size measurements are then explored to understand seeker operation in poor weather. Size measures cannot easily be used for moving targets, where the target signature is distorted and displaced. The ability to detect, segment and measure vehicle dimensions and velocity from the shadows of moving targets is tested using real and simulated data. The choice of polarisation can affect the quality of measurements and the ability to reject clutter. Data from three different radars is examined to help to understand the performance using linear and circular polarisations. For sensors operating at shorter ranges, the application of elevation monopulse to include target height as a discriminant is tested, showing good potential on simulated data. The combination of these studies offers an insight into the performance factors that influence the design and processing of a radar seeker. The use of shadow imagery on short-dwell radar seeker imagery is an area offering particular promise

ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications

Twelve edited original papers on the latest and state-of-art results of topics ranging from calibration, validation, and science to a wide range of applications using ALOS-2/PALSAR-2. We hope you will find them useful for your future research

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