Small Baseline Subset (SBAS) pixel density vs. geology and land use in semi-arid regions in Syria

36 ENVISAT ASAR images acquired in 2002 to 2010 along descending passes with nominal revisiting time of 35 days were processed over the whole region of Homs, western Syria, by implementing the low-pass Small Baseline Subset (SBAS) technique. More than 280,000 coherent pixels with ~100m ground resolution were obtained. We analysed pixel spatial distribution in respect of local geology and land use, to assess to what extent these factors can influence the performance of an interferometric deformation analysis in a semi-arid environment. Filtering out the amount of pixels associated with the urban fabric of Homs and surrounding villages, it is apparent that limestone and marl units are less prone to generate coherent pixels if compared with the basalt units in the north-western sector of the processed region. The latter resulted in pixel density of ~50-60 pixels/km2, which is comparable with that found over urban settlements and man-made structures

On the use of the ISBAS Acronym in InSAR Aapplications. Comment on Vajedian, S.; Motagh, M.; Nilfouroushan, F. StaMPS Improvement for Deformation Analysis in Mountainous Regions: Implications for the Damavand Volcano and Mosha Fault in Alborz. Remote Sens. 2015, 7, 8323–8347

Vajedian et al. [1] present an improved method for the derivation of deformation parameters using satellite Interferometric Synthetic Aperture Radar (InSAR) data. The method is a modification of the Small Baseline Subset (SBAS) method as implemented in the StaMPS (Stanford Method for Persistent Scatterers) software. The modification includes many steps including the filtering of the differential interferograms, integration with GPS data and advanced phase unwrapping “to overcome a lot of short- and long-wavelength artifacts that are clearly visible in StaMPS results” (cf. [1], p. 8331). The authors refer to this new approach as the Improved SBAS, or ISBAS, method. [...

Study of groundwater properties and behaviour using geospatial techniques

Groundwater contributes a significant proportion of the earth’s freshwater and is essential to sustain life on earth, but its availability in spatial and temporal dimensions is not uniform. With the advent of efficient pumps and rural electrification, global groundwater extraction increased from 312 km3/year in the 1960s to 800 km3/year in 2000s; approximately 70% of this extraction is used for agriculture. About half of domestic human water consumption in urban areas is from groundwater. The ever-increasing dependence on groundwater has led to its depletion across various parts of the world. This trend must be reversed to sustain the critical role of groundwater. Groundwater monitoring based on validated data can provide information that can guide decision making to decrease groundwater stress on local and global scales. This thesis aims to monitor spatio-temporal changes in groundwater and related phenomena (like land subsidence) using geospatial techniques like InSAR, GRACE, GIS, data analysis and data visualisation. The over-extraction or rebound of groundwater can lead to land deformation because of the change in effective stress of underground sediments. Groundwater-induced land movement can cause damage to property and resources, and hence it must be monitored for the safety and economics of a city. This thesis explores the suitability of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) to measure land deformation and different senor-software for InSAR processing. The groundwater quantity variation and resulting land deformation for London using InSAR and Gravity Recovery and Climate Experiment (GRACE) between 2002-2010 were analysed. Long-term, decreasing, complex, non-linear patterns in the spatial and temporal domains from both InSAR and GRACE datasets were observed. The land movement velocities varied from -6 to +6 mm/year, and their reliability was validated with observed GNSS data by conducting a two-sample t-test. The average groundwater loss estimated from GRACE was found to be 9.003 MCM/year. The results demonstrate that InSAR and GRACE complement each other and can be an excellent source of monitoring groundwater for hydrologists. Then groundwater induced subsidence for London and the National Capital Territory of Delhi (NCT-Delhi) between 2016 and 2020 were studied. The land movement velocities were found to vary between -24 mm/year to +24 mm/year for London and between -18 mm/year to +30 mm/year for NCT-Delhi. This land movement was compared with observed groundwater levels and spatio-temporal variation of groundwater. A 1-D mathematical model was used to quantify land deformation for a given change in groundwater level. It was broadly observed that when large volumes of groundwater are extracted, it leads to land subsidence, and when groundwater is recharged, surface uplift is witnessed. However the local geology, did play an important role in the extent of subsidence, which was considered in the mathematical model. The increased pressure on groundwater can cause spatio-temporal changes in its quality because of various atmospheric stimulations, varied geology, variation in subsurface mineralogy and factors controlling residence times. Moreover, the variation of groundwater quality is vital for the sustainable management and safety of groundwater. Thus, the variation in groundwater quality is analysed from observed data for London between 2000 and 2020. The data samples were used from 500 wells in the London basin, and the data is provided in the free open access domain by Environment Agency. The overall groundwater in London was found to be dominant magnesium bicarbonate type which typically represents shallow fresh groundwater, and spatio-temporal variations of hardness, sodium, and dissolved oxygen (DO) were also studied. Significant variations in the range of each constituent were found, which was attributed to variation in the geology of the London Palaeogene aquifers and anthropogenic activities. All the case studies help better understand the phenomenon of spatio-temporal variation in groundwater behaviour and associated land deformation for urban cities. The research presented in this thesis can be used to determine whether groundwater is available and suitable for its intended purpose, discover pollutants, examine any spatio-temporal variations, and monitor land subsidence

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

Book of short Abstracts of the 11th International Symposium on Digital Earth

The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

The Effect of Hydrology on Soil Erosion

This Special Issue includes manuscripts about soil erosion and degradation processes and the accelerated rates due to hydrological processes and climate change. The new research included in this issue focuses on measurements, modeling, and experiments in field or laboratory conditions developed at different scales (pedon, hillslope, and catchment). This Special Issue received investigations from different parts of the world such as Ethiopia, Morocco, China, Iran, Italy, Portugal, Greece, and Spain, among others. We are happy to see that all papers presented findings characterized as unconventional, provocative, innovative, and methodologically new. We hope that the readers of the journal Water can enjoy and learn about hydrology and soil erosion using the published material, and share the results with the scientific community, policymakers, and stakeholders to continue this amazing adventure, facing plenty of issues and challenges

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