Calibration Instrumentation for the Hydrogen Intensity and Real-Time Analysis eXperiment

The Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) is a 21 cm neutral hydrogen intensity mapping experiment to be deployed in the Karoo Desert in South Africa. It aims to improve constraints on the dark energy equation of state through measurements of large-scale structure at high redshift, while doubling as a state-of-the-art fast radio burst (FRB) detector. This dissertation focuses on two aspects of the HIRAX instrument characterization: (1) optimizing the signal-to-noise of antennas, through the design and implementation of a custom test-bed for determining the noise temperature of radio antennas operating between 400-800MHz, and (2) mapping the HIRAX telescope beam pattern with a custom drone calibration system. The work described is critical to HIRAX\u27s development, both by informing final antenna design and providing the tools to generate beam maps that will factor into all cosmological analysis

Modeling Boundaries of Influence among Positional Uncertainty Fields

Within a CIS environment, the proper use of information requires the identification of the uncertainty associated with it. As such, there has been a substantial amount of research dedicated to describing and quantifying spatial data uncertainty. Recent advances in sensor technology and image analysis techniques are making image-derived geospatial data increasingly popular. Along with development in sensor and image analysis technologies have come departures from conventional point-by-point measurements. Current advancements support the transition from traditional point measures to novel techniques that allow the extraction of complex objects as single entities (e.g., road outlines, buildings). As the methods of data extraction advance, so too must the methods of estimating the uncertainty associated with the data. Not only will object uncertainties be modeled, but the connections between these uncertainties will also be estimated. The current methods for determining spatial accuracy for lines and areas typically involve defining a zone of uncertainty around the measured line, within which the actual line exists with some probability. Yet within the research community, the proper shape of this \u27uncertainty band\u27 is a topic with much dissent. Less contemplated is the manner in which such areas of uncertainty interact and influence one another. The development of positional error models, from the epsilon band and error band to the rigorous G-band, has focused on statistical models for estimating independent line features. Yet these models are not suited to model the interactions between uncertainty fields of adjacent features. At some point, these distributed areas of uncertainty around the features will intersect and overlap one another. In such instances, a feature\u27s uncertainty zone is defined not only by its measurement, but also by the uncertainty associated with neighboring features. It is therefore useful to understand and model the interactions between adjacent uncertainty fields. This thesis presents an analysis of estimation and modeling techniques of spatial uncertainty, focusing on the interactions among fields of positional uncertainty for image-derived linear features. Such interactions are assumed to occur between linear features derived from varying methods and sources, allowing the application of an independent error model. A synthetic uncertainty map is derived for a set of linear and aerial features, containing distributed fields of uncertainty for individual features. These uncertainty fields are shown to be advantageous for communication and user understanding, as well as being conducive to a variety of image processing techniques. Such image techniques can combine overlapping uncertainty fields to model the interaction between them. Deformable contour models are used to extract sets of continuous uncertainty boundaries for linear features, and are subsequently applied to extract a boundary of influence shared by two uncertainty fields. These methods are then applied to a complex scene of uncertainties, modeling the interactions of multiple objects within the scene. The resulting boundary uncertainty representations are unique from the previous independent error models which do not take neighboring influences into account. By modeling the boundary of interaction among the uncertainties of neighboring features, a more integrated approach to error modeling and analysis can be developed for complex spatial scenes and datasets

Precise Point Positioning Augmentation for Various Grades of Global Navigation Satellite System Hardware

The next generation of low-cost, dual-frequency, multi-constellation GNSS receivers, boards, chips and antennas are now quickly entering the market, offering to disrupt portions of the precise GNSS positioning industry with much lower cost hardware and promising to provide precise positioning to a wide range of consumers. The presented work provides a timely, novel and thorough investigation into the positioning performance promise. A systematic and rigorous set of experiments has been carried-out, collecting measurements from a wide array of low-cost, dual-frequency, multi-constellation GNSS boards, chips and antennas introduced in late 2018 and early 2019. These sensors range from dual-frequency, multi-constellation chips in smartphones to stand-alone chips and boards. In order to be comprehensive and realistic, these experiments were conducted in a number of static and kinematic benign, typical, suburban and urban environments. In terms of processing raw measurements from these sensors, the Precise Point Positioning (PPP) GNSS measurement processing mode was used. PPP has become the defacto GNSS positioning and navigation technique for scientific and engineering applications that require dm- to cm-level positioning in remote areas with few obstructions and provides for very efficient worldwide, wide-array augmentation corrections. To enhance solution accuracy, novel contributions were made through atmospheric constraints and the use of dual- and triple-frequency measurements to significantly reduce PPP convergence period. Applying PPP correction augmentations to smartphones and recently released low-cost equipment, novel analyses were made with significantly improved solution accuracy. Significant customization to the York-PPP GNSS measurement processing engine was necessary, especially in the quality control and residual analysis functions, in order to successfully process these datasets. Results for new smartphone sensors show positioning performance is typically at the few dm-level with a convergence period of approximately 40 minutes, which is 1 to 2 orders of magnitude better than standard point positioning. The GNSS chips and boards combined with higher-quality antennas produce positioning performance approaching geodetic quality. Under ideal conditions, carrier-phase ambiguities are resolvable. The results presented show a novel perspective and are very promising for the use of PPP (as well as RTK) in next-generation GNSS sensors for various application in smartphones, autonomous vehicles, Internet of things (IoT), etc

Evaluating Multi-Temporal DInSAR Measurements of Ground Surface Deformation Around the Rhenish Coalfields in Germany Using Sentinel-1 SAR Imagery

Ground surface deformation caused by land subsidence is a critical aspect when assessing safety and environmental impacts of open-pit mining operations. These mining-induced deformations can cause severe damage to local infrastructure and buildings located in the region. Monitoring mining operations using traditional techniques is laborious, costly and time consuming, with many locations being difficult to access. As a result, in-situ observations of surface movement and structural stability are often sparsely completed along areas of high risk or concern. Remote sensing observations facilitate a reliable, temporally and spatially continuous monitoring process of mining operations, regardless of physical accessibility, at large scales with minimal cost. In this study, two commonly used C-band Differential Interferometric Synthetic Aperture Radar (DInSAR) methods, namely Small Baseline Subset (SBAS) and Persistent Scatterer Interferometry (PSI), are applied to Sentinel-1 data to show consistency when observing land displacement in the Rhenish coalfields region in Germany. Deformation rates around the Rhenish coalfields are assessed for 2015 and 2016, independently, using both techniques and compared using GNSS station data of three nearby stations part of the EUREF network. The primary focus on this study is to determine the performance differences between the two techniques. The PSI deformation estimates showed significantly lower variation in measurements but had a severely limited spatial coverage compared to the SBAS estimates. Comparison of annual deformation rates measured by the two techniques showed a stronger agreement for 2016 (RMSE = 8.7 mm/year) than 2015 (RMSE = 26 mm/year). The discrepancy between annual comparisons is caused by overestimation of surface subsidence rates by the 2015 SBAS measurements. This overestimation is likely the result of atmospheric artefacts propagating into the phase unwrapping due to a lack of sufficient SAR scenes available in 2015. It was determined that the SBAS technique benefits more heavily from additional data and when data is limited, the PSI technique proves to be more reliable for measuring annual deformation rates. Despite this, both techniques observed similar overall deformation patterns across the landscape but reported different magnitude of deformation; commonly observed in other studies. The two methods showed stronger agreement over targets characterized as hard impermeable surfaces (e.g. built-up areas). Although only one of the three publicly available GNSS sites coincided with the InSAR study domain, when compared with base station GNSS sites, the DInSAR estimates are within the uncertainty range of the GNSS measurements, indicating good potential. This thesis illustrates the applicability of using satellite remote sensing observations to monitor mining-induced surface deformations to supplement traditional monitoring techniques

Rice Plant Height Monitoring from Space with Bistatic Interferometry

This chapter provides an overview of the possibility to derive paddy rice plant heights with spaceborne bistatic SAR interferometry (InSAR). By using the only available interferometer in space, TanDEM-X, an investigation of rice crops located in Turkey is performed. Before analyzing the main outcomes, an introduction to the generation of elevation models with InSAR is provided, with a special focus on the agricultural land cover. The processing chain and the modifications foreseen to properly produce plant elevations and a roadmap for the quality assessment are described. The results obtained, with a very high interferometric coherence supporting an accurate estimation due to a limited electromagnetic wave penetration into the canopy, support a temporal change analysis on a field-by-field basis. For the purpose, an automatic approach to segment the fields without external auxiliary data is also provided. The study is concluded with an analysis of the impact of the wave polarization in the results

Twenty years of progress: GIScience in 2010

It is 20 years since the term “geographic information science” was suggested to encompass the set of fundamental research issues that surround GIS. Two decades of GIScience have produced a range of accomplishments, in an expanding literature of research results as well as in the infrastructure of research. Several themes are suggested for future research, based both on gaps in what has been accomplished thus far, and on technology trends that will themselves raise research questions

Using Sound to Represent Uncertainty in Spatial Data

There is a limit to the amount of spatial data that can be shown visually in an effective manner, particularly when the data sets are extensive or complex. Using sound to represent some of these data (sonification) is a way of avoiding visual overload. This thesis creates a conceptual model showing how sonification can be used to represent spatial data and evaluates a number of elements within the conceptual model. These are examined in three different case studies to assess the effectiveness of the sonifications. Current methods of using sonification to represent spatial data have been restricted by the technology available and have had very limited user testing. While existing research shows that sonification can be done, it does not show whether it is an effective and useful method of representing spatial data to the end user. A number of prototypes show how spatial data can be sonified, but only a small handful of these have performed any user testing beyond the authors’ immediate colleagues (where n > 4). This thesis creates and evaluates sonification prototypes, which represent uncertainty using three different case studies of spatial data. Each case study is evaluated by a significant user group (between 45 and 71 individuals) who completed a task based evaluation with the sonification tool, as well as reporting qualitatively their views on the effectiveness and usefulness of the sonification method. For all three case studies, using sound to reinforce information shown visually results in more effective performance from the majority of the participants than traditional visual methods. Participants who were familiar with the dataset were much more effective at using the sonification than those who were not and an interactive sonification which requires significant involvement from the user was much more effective than a static sonification, which did not provide significant user engagement. Using sounds with a clear and easily understood scale (such as piano notes) was important to achieve an effective sonification. These findings are used to improve the conceptual model developed earlier in this thesis and highlight areas for future research

Analysis and mitigation of site-dependent effects in static and kinematic GNSS applications

Satellitensignale unterliegen auf ihrem Weg von der Satelliten- zur Empfangsantenne einer Vielzahl an Einflüssen die zu Abweichungen führen. Heutzutage stellen in vielen Anwendungsbereichen insbesondere die stationsspezifischen Anteile, welche sich in Mehrwegeeffekte aus dem Fernfeld, NLOS-Empfang und Signalbeugung, den Einfluss der Satellitengeometrie und Antennennahfeldeffekte untergliedern lassen, einen der genauigkeitsbegrenzenden Faktoren in der satellitengestützten Positionsbestimmung dar. Dies ist dadurch begründet, dass durch die Abhängigkeit von der individuell vorliegenden Antennenumgebung eine Minimierung der Einflüsse erheblich erschwert wird und etablierte Strategien, wie beispielsweise die Differenzbildung in relativen Positionierungsansätzen, in der Regel nicht anwendbar sind. Obwohl diese Effekte bereits seit den frühesten Entwicklungen auf dem Gebiet der satellitengestützten Positionsbestimmung untersucht wurden, ist eine vollumfängliche Lösungsstrategie auch in der heutigen Zeit noch nicht verfügbar. Daher hat diese Thematik nicht an Relevanz verloren und es besteht noch immer der Bedarf an weiteren Untersuchungen zur Vertiefung des Verständnisses und zur Erweiterung des Portfolios an verfügbaren Minimierungsansätzen. In dieser Arbeit werden die vier unterschiedlichen Effekte vor dem Hintergrund der hochpräzisen Positionsbestimmung in statischen und kinematischen GNSS-Anwendungen adressiert. Der wesentliche Fokus der Untersuchungen liegt hierbei auf der Detektion und Elimination betroffener Satellitensignale durch die Einbindung detaillierter Umgebungsmodelle aus terrestrischen Messverfahren. Auf Basis dieser methodischen und empirischen Analysen lassen sich für die einzelnen Effekte vier Hauptaspekte herausstellen: (1) Da Antennennahfeldeffekte primär den Messsensor selbst beeinflussen und folglich die angestrebte Detektion und Elimination zur Minimierung nicht geeignet ist, wird alternativ die Minimierung des Einflusses durch spezielle Antennenaufbauten empirisch analysiert. Daraus resultierend werden mit exakt identischen Antennenaufbauten erreichbare Genauigkeiten im Submillimeterbereich nachgewiesen. (2) Der Einfluss auf die Positionsgenauigkeit der potentiell durch eine Signalelimination hervorgerufenen Verschlechterung der Satellitengeometrie kann durch Simulationen generischer Abschattungsszenarien als unkritisch identifiziert werden. Darüber hinaus wird eine Methode zur Integration der Qualität der Satellitengeometrie in die Wegpunktplanung von UAVs entwickelt, welche sowohl in der Planungsphase, als auch während des UAV-Fluges eine Anpassung und Optimierung der Flugroute ermöglicht. (3) Auf Basis mittels terrestrischer Laserscanner erzeugter Punktwolken wird eine Methode zur Erzeugung von Elevationsmasken entwickelt, welche adaptiv gegenüber der vorliegenden Antennenumgebung sind und eine effektive Detektion und Elimination von Satellitensignalen erlauben, die NLOS-Empfang oder Signalbeugung unterliegen. Diese Minimierungsstrategie ist sowohl in statischen, als auch kinematischen Anwendungen einsetzbar und ermöglicht bei zusätzlicher Einbindung von Fresnel Zonen auch die Berücksichtigung der Ausbreitungseigenschaften elektromagnetischer Wellen. (4) Als vorbereitender Schritt für die Entwicklung von Methoden zur Detektion und Eliminierung von Fernfeld-Mehrwegeeffekten werden die Voraussetzungen für die Entstehung der Effekte untersucht. Durch Vergleich simulierter und beobachteter SNR-Zeitreihen und der Berücksichtigung von Fresnel Zonen kann eine Überlappung von 50% zwischen Fresnel-Zone und Reflektorfläche als bereits ausreichend für eine potentielle Mehrwegebelastung identifiziert werden. In der Gesamtbetrachtung liefern die in dieser Arbeit gewonnenen Erkenntnisse und entwickelten Methoden einen relevanten Beitrag zu dem übergeordneten Ziel einer ganzheitlichen Minimierung stationsspezifischer Abweichungen und ermöglichen so eine signifikante Verbesserung der Positionsgenauigkeit unter schwierigen GNSS-Bedingungen. Darüber hinaus nimmt diese Arbeit den in den letzten Jahren forcierten Trend von einer punktweisen zu einer flächenhaften Objekterfassung an, indem das Potenzial einer detaillierten und effizienten Erfassung der Antennenumgebung mittels terrestrischer Laserscanner zur Minimierung und Analyse stationsspezifischer Abweichungen bei der satellitengestützten Positionsbestimmung aufzeigt und genutzt wird.Satellite signals are subject to various error sources on their way from the satellite to the receiving antenna. Nowadays, in many fields of application, the site-dependent parts, which can be separated into far-field multipath, NLOS reception and signal diffraction, the influence of the satellite geometry and antenna near-field effects, are one of the accuracy limiting factors in satellite-based positioning. This is due to the fact that the dependence on the individual antenna environment considerably impedes a minimization of the influences and established strategies, such as double-differencing in relative positioning approaches, are generally not applicable. Although these effects have been subject to scientific research since the earliest developments in the field of satellite-based positioning, an all-embracing solution is still lacking. Therefore, this topic has not lost its relevance and there is still a need for further investigations to deepen the understanding and expanding the portfolio of available mitigation techniques. In this dissertation, the four different effects are addressed against the background of high-precision static and kinematic GNSS applications. In this context, the main focus of the investigations is on the detection and exclusion of affected satellite signals, by integrating detailed environment models derived from terrestrial measurements. Based on these methodological and empirical analyses, four main aspects can be highlighted for the different effects: (1) Since antenna near-field effects primarily affect the measuring sensor itself, and thus, the striven detection and exclusion for mitigation is not applicable in this case, alternatively the mitigation of the influence by special antenna setups is empirically analyzed. As a result, achievable accuracies in the sub-millimeter range can be demonstrated using exactly identical antenna setups. (2) By simulating generic obstruction scenarios, the influence on the positional accuracy of the deterioration of the satellite geometry, potentially caused by an elimination of satellite signals, can be identified as uncritical. Furthermore, a method for integrating measures for the quality of the satellite geometry in the waypoint planning of UAVs is developed, which enables the adaption and optimization of the flight route in the planning phase, as well as during the UAV flight. (3) Based on point clouds of terrestrial laser scanners, a method for the determination of elevation masks that are adaptive to the present antenna environment is developed, which enables an effective detection and exclusion of signals that are subject to NLOS reception or signal diffraction. This mitigation strategy can be applied to static and kinematic GNSS applications and by additionally integrating Fresnel zones, also the propagation characteristics of electromagnetic waves are considered. (4) As a preparatory step for the development of methods for detecting and excluding far-field multipath, the prerequisites for the occurrence of the effect are investigated. By comparison of simulated and observed SNR time series and by considering Fresnel zones, an overlap of 50% between Fresnel zone and reflecting surface can be identified as already being sufficient for potential far-field multipath influences. In the overall view, the findings and methods developed in this dissertation represent a relevant contribution to the superordinate goal of a holistic mitigation of site-dependent effects, and thus, enable a significant improvement of the positional accuracy under difficult GNSS conditions. In addition, this thesis adopts the currently forced trend from a pointwise to an area-based object acquisition by revealing and exploiting the potential of a detailed and efficient acquisition of the antenna environment by terrestrial laser scanners for mitigating and analyzing site-dependent effects in satellite based positioning applications

The Influence of Measurement Scale and Uncertainty on Interpretations of River Migration

Environmental scientists increasingly use remotely-sensed images to measure how rivers develop over time and respond to upstream changes in environmental drivers such as land use, urbanization, deforestation and agricultural practices. These measurements are subject to uncertainty that can bias conclusions. The first step towards accurate interpretation of river channel change is properly quantifying and accounting for uncertainty involved in measuring changes in river morphology. In Chapter 2 we develop a comprehensive framework for quantifying uncertainty in measurements of river change derived from aerial images. The framework builds upon previous uncertainty research by describing best practices and context-specific strategies, comparing each approach and outlining how to best handle measurements that fall below the minimum level of detection. We use this framework in subsequent chapters to reduce the impact of erroneous measurements. Chapter 3 evaluates how the time interval between aerial images influences the rates at which river channels appear to laterally migrate across their floodplains. Multiple lines of evidence indicate that river migration measurements obtained over longer time intervals (20+ years) will underestimate the ‘true’ rate because the river channel is more likely to have reversed the direction of migration, which erases part of the record of gross erosion as seen from aerial images. If the images don’t capture channel reversals and periodic episodes of fast erosion, the river appears to have migrated a shorter distance (which corresponds to a slower rate) than reality. Obtaining multiple measurements over shorter time intervals (\u3c 5 years) and limiting direct comparisons to similar time intervals can reduce bias when inferring how river migration rates may have changed over time. Chapter 4 explores the physical processes governing the relationship between river curvature and the rate of river migration along a series of meander bends. We used fine-scale empirical measurements and geospatial analyses to confirm theory and models indicating that migration and curvature exhibit a monotonic relationship. The results will improve models seeking to emulate river meander migration patterns

Analysis and visualisation of digital elevation data for catchment management

River catchments are an obvious scale for soil and water resources management, since their shape and characteristics control the pathways and fluxes of water and sediment. Digital Elevation Models (DEMs) are widely used to simulate overland water paths in hydrological models. However, all DEMs are approximations to some degree and it is widely recognised that their characteristics can vary according to attributes such as spatial resolution and data sources (e.g. contours, optical or radar imagery). As a consequence, it is important to assess the ‘fitness for purpose’ of different DEMs and evaluate how uncertainty in the terrain representation may propagate into hydrological derivatives. The overall aim of this research was to assess accuracies and uncertainties associated with seven different DEMs (ASTER GDEM1, SRTM, Landform Panorama (OS 50), Landform Profile (OS 10), LandMap, NEXTMap and Bluesky DTMs) and to explore the implications of their use in hydrological analysis and catchment management applications. The research focused on the Wensum catchment in Norfolk, UK. The research initially examined the accuracy of the seven DEMs and, subsequently, a subset of these (SRTM, OS 50, OS10, NEXTMap and Bluesky) were used to evaluate different techniques for determining an appropriate flow accumulation threshold to delineate channel networks in the study catchment. These results were then used to quantitatively compare the positional accuracy of drainage networks derived from different DEMs. The final part of the thesis conducted an assessment of soil erosion and diffuse pollution risk in the study catchment using NEXTMap and OS 50 data with SCIMAP and RUSLE modelling techniques. Findings from the research demonstrate that a number of nationally available DEMs in the UK are simply not ‘fit for purpose’ as far as local catchment management is concerned. Results indicate that DEM source and resolution have considerable influence on modelling of hydrological processes, suggesting that for a lowland catchment the availability of a high resolution DEM (5m or better) is a prerequisite for any reliable assessment of the consequences of implementing particular land management measures. Several conclusions can be made from the research. (1) From the collection of DEMs used in this study the NEXTMap 5m DTM was found to be the best for representing catchment topography and is likely to prove a superior product for similar applications in other lowland catchments across the UK. (2) It is important that error modelling techniques are more routinely employed by GIS users, particularly where the fitness for purpose of a data source is not well-established. (3) GIS modelling tools that can be used to test and trial alternative management options (e.g. for reducing soil erosion) are particularly helpful in simulating the effect of possible environmental improvement measures