Wetlands have been heavily affected by human-alteration, this is done to drain thewetland so that the ground can be used for other purposes such as forestry oragriculture. With high accuracy data available now, it is possible to use differentmethods automatically to identify these ditches in wetlands or other areas. Fourdifferent methods were applied to two areas to delineate ditches. To compare the different methods, the results were quantified by comparing with amanually created map of the ditches. Drainage density and an agreement index wereused. The results indicate that the methods of impoundment index and map gullydepth are best able to distinguish the ditches in wetlands. The former gave a betterresult on areas inside wetlands while the latter gave a better result with non-wetlandareas. The other two methods make mistakes and misjudgements that givemisleading results, they ignore ditches partially or completely, or finds ditches inareas without them. Even so, all methods are at least a clear improvement over thecurrently available property map's water flows, but not in the same class as the timeconsumingmanual method. / Våtmarker har påverkats mycket av människan genom dikning, detta görs för attdränera våtmarken så att marken kan användas för andra syften som skogsbruk ellerjordbruk. Med höjddata i hög noggrannhet som nu finns tillgänglig är det möjligt attanvända olika metoder för att urskilja dessa diken i våtmarker. Fyra olika metodermed applicerades på två olika områden för att undersöka möjligheten att urskiljadiken. För att jämföra de olika metoderna kvantifieras resultaten genom att jämföras meden manuellt skapad karta över diken. Dränerings densitet och ettöverensstämmelseindex användes. Resultaten pekar på att metoderna fördämningsindex (impoundment index) och ravindjupskartering (map gully depth) klarar bäst avatt urskilja diken i våtmarker. Där den föregående ger ett gav ett bättre resultat inomvårmarker och den senare gav ett bättre resultat generellt över området. De tvåandra metoderna gör missar och felbedömningar som ger missvisande resultat.Oavsett det, så är karteringen av dikena i nuläget en klar förbättring överFastighetskartans vattenflöden, men inte i samma klass som den tidskrävandemanuella metoden.

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Life on early earth has long been the topic of discussion for many researchers: how did it come to be? Which cells came first? Where can we find them? The most ancient rocks on our planet may hold some of the answers to these questions, but many may only be answered in laboratories. Chemical and morphological traces can be found from Archaean deposits, tantalisingly similar to modern day prokaryotes. Often, they are interpreted as the fossilised remains of bacteria or archaea. However, the caveat remains the abiotic mechanisms with which many similar traces and markers can be formed. The purpose of this thesis was to look into the similarities and differences in abiotic and biological formation of filamentous structures in rocks and observe whether there are chemical or morphological factors that allow for distinguishing between the two. Various laboratory methods were used: chemical gardens to form filamentous abiotic structures and experimental mineralisation of a filamentous methanogen in carbonate, phosphate, and silicate in order to compare and contrast the various mineralisation mechanisms in the fidelity of preservation of the microbes. In the former experiment, analysis with electron paramagnetic resonance (EPR) spectroscopy was carried out to identify potential chemical biomarkers. A combination of scanning and transmission electron microscopy, energy dispersive X-ray (EDX) analysis, X-ray diffraction (XRD) and Raman spectroscopy were also used to analyse the minerals and precipitates formed in both sets of experiments. The results of this research indicate that morphology of filamentous structures and the chemical signatures in biominerals may not be reliable as biogenic indicators. Furthermore, the work on experimental mineralisation reveals the possible biases in the rock record of microbial preservation which is highly dependent on the structure of the cell wall, chemistry of the environment, and the mineral formed. Finally, this work has important outcomes for the search for biomarkers on earth and on other planets and for the recognition of pseudofossils versus microbial fossils in the rock record.

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The senseFly eBeePlus fixed-wing drone is a market available UAV compatible with a range of sensors that includes the Parrot Sequoia+ multispectral camera. Commercial applications of the drone predominantly focus on agriculture, environmental management, and engineering applications. The Sequoia 4-band multispectral sensor with bands optimised for plant health analysis, has a spectral range that coincides with the absorption features of iron. Previous studies with the use of hyperspectral sensors on multicopter UAVs have proven successful in the detection and delineation of hydroxides and sulphates associated with weathering of sulphides at the surface. This study aims to evaluate the ability of the eBeePlus drone equipped with a Parrot Sequoia+ sensor to effectively detect and delineate surficial sulphide mineral expressions by testing its capability on a known nickel-copper mineralisation occurrence at Illukunnguaq, on the north-western coast of Disko Island, West Greenland. Formally hosting a 28-tonne nickeliferous pyrrhotite massive sulphide boulder, many companies have sought this region for a possible extension of the mineralisation or another local mineral occurrence. Iron-feature band ratios and Spectral Angle Mapping (SAM) are two methods tested to first characterise the known occurrence, then search the wider region for other features with a similar signature as the Illukunnguaq dyke. To assist the evaluation and fine tune the Sequoia sensor, it will be compared against the trialled and trusted Rikola hyperspectral sensor, proven to map iron features. In addition, eigen maxima as one of many geomorphological indices that utilise the co-product Digital Surface Model (DSM) of the spectral survey, is employed to assess whether the Illukunnguaq dyke and other features are structurally mappable.  Results show that the Sequoia multispectral sensor, albeit less spectrally resolved than the Rikola hyperspectral sensor was able to detect surficial sulphide mineral expressions both by applying iron-feature band ratios and SAM. The latter was performed using laboratory measured and open-access library spectra. To fine-tune the tools compatible with the Sequoia sensor, in-depth investigations into iron-feature band ratio index values and best-fit library spectra for SAM was conducted. Confidence was increased by the blind detection of another known exposure and permitted a regional search to find additional features with spectral similarities to the Illukunnguaq dyke for future ground truthing. This study demonstrates that the eBeePlus drone can be used for mineral exploration when iron-sulphides are a part of the mineral system and outcropping at the surface. Leading field programs with detailed multispectral mapping can improve the efficiency of geologists by generating or verifying targets prior to ‘boots-on-the-ground’ geological sampling or mapping.

This project provides research and insight towards expanding the ETSU at Rome Program into a larger multidisciplinary study abroad program. The program's goal is to evolve from its presummer session with a one-course offering curriculum into a multidisciplinary, multicourse study abroad program for both the presummer session and entire summer session. Research and analysis have been conducted to discover best practices for study abroad programs in surrounding institutions. Additionally, in expansion upon existing efforts, this research helps seek out partnerships and collaborations within the institution and outside the institution. Professors from numerous departments throughout ETSU have been interviewed regarding their position and views of study abroad programs for students within their departments. Data have also been gathered to help better understand the potential and existing funding opportunities in a study abroad program. Additionally, other opportunities for growth and expansion and the challenges associated with these have been studied.

Recent interest surrounding large scale satellite constellations has increased analysis efforts to create the most efficient designs. Multiple studies have successfully optimized constellation patterns using equations of motion propagation methods and genetic algorithms to arrive at optimal solutions. However, these approaches are computationally expensive for large scale constellations, making them impractical for quick iterative design analysis. Therefore, a minimalist algorithm and efficient computational method could be used to improve solution times. This thesis will provide a tool for single target constellation optimization using spherical trigonometry propagation, and an evolutionary genetic algorithm based on a multi-objective optimization function. Each constellation will be evaluated on a normalized fitness scale to determine optimization. The performance objective functions are based on average coverage time, average revisits, and a minimized number of satellites. To adhere to a wider audience, this design tool was written using traditional Matlab, and does not require any additional toolboxes. To create an efficient design tool, spherical trigonometry propagation will be utilized to evaluate constellations for both coverage time and revisits over a single target. This approach was chosen to avoid solving complex ordinary differential equations for each satellite over a long period of time. By converting the satellite and planetary target into vectors of latitude and longitude in a common celestial sphere (i.e. ECI), the angle can be calculated between each set of vectors in three-dimensional space. A comparison of angle against a maximum view angle, , controlled by the elevation angle of the target and the satellite’s altitude, will determine coverage time and number of revisits during a single orbital period. Traditional constellations are defined by an altitude (a), inclination (I), and Walker Delta Pattern notation: T/P/F. Where T represents the number of satellites, P is the number of orbital planes, and F indirectly defines the number of adjacent planes with satellite offsets. Assuming circular orbits, these five parameters outline any possible constellation design. The optimization algorithm will use these parameters as evolutionary traits to iterate through the solutions space. This process will pass down the best traits from one generation to the next, slowly evolving and converging the population towards an optimal solution. Utilizing tournament style selection, multi-parent recombination, and mutation techniques, each generation of children will improve on the last by evaluating the three performance objectives listed. The evolutionary algorithm will iterate through 100 generations (G) with a population (n) of 100. The results of this study explore optimal constellation designs for seven targets evenly spaced from 0° to 90° latitude on Earth, Mars and Jupiter. Each test case reports the top ten constellations found based on optimal fitness. Scatterplots of the constellation design solution space and the multi-objective fitness function breakdown are provided to showcase convergence of the evolutionary genetic algorithm. The results highlight the ratio between constellation altitude and planetary radius as the most influential aspects for achieving optimal constellations due to the increased field of view ratio achievable on smaller planetary bodies. The multi-objective fitness function however, influences constellation design the most because it is the main optimization driver. All future constellation optimization problems should critically determine the best multi-objective fitness function needed for a specific study or mission.

In today's competitive manufacturing industries, companies strive to reduce manufacturing development costs and lead times in hopes of reducing costs and capturing more market share from early release of their new or redesigned products. Tooling lead time constraints are some of the more significant challenges facing product development of advanced free-form components. This is especially true for complex designs in which large dies, molds or other large forming tools are required. The lead time for tooling, in general, consists of three main components; material acquisition, tool design and engineering, and tool manufacturing. Lead times for material acquisition and tool manufacture are normally a function of vendor/outsourcing constraints, manufacturing techniques and complexity of tooling being produced. The tool design and engineering component is a function of available manpower, engineering expertise, type of design problem (initial design or redesign of tooling), and complexity of the design problem. To reduce the tool design/engineering lead time, many engineering groups have implemented Computer-Aided Design, Engineering, and Manufacturing (CAD/CAE/CAM or CAx) tools as their standard practice for the design and analysis of their products. Although the predictive capabilities are efficient, using CAx tools to expedite advanced die design is time consuming due to the free-form nature and complexity of the desired part geometry. Design iterations can consume large quantities of time and money, thus driving profit margins down or even being infeasible from a cost and schedule standpoint. Any savings based on a reduction in time are desired so long as quality is not sacrificed. This thesis presents an automated tool design methodology that integrates state-of-the-art numerical surface fitting methods with commercially available CAD/CAE/CAM technologies and optimization software. The intent is to virtually create tooling wherein work-piece geometries have been optimized producing products that capture accurate design intent. Results show a significant reduction in design/engineering tool development time. This is due to the integration and automation of associative tooling surfaces automatically derived from the known final design intent geometry. Because this approach extends commercially available CAx tools, this thesis can be used as a blueprint for any automotive or aerospace tooling need to eliminate significant time and costs from the manufacture of complex free-form components.

A significant challenge in the design of multidisciplinary systems (e.g., airplanes, robots, cell phones) is to predict the effects of design decisions at the time these decisions are being made early in the design process. These predictions are used to choose among design options and to validate design decisions. System behavioral models, which predict a system's response to stimulus, provide an analytical method for evaluating a system's behavior. Because multidisciplinary systems contain many different types of components that have diverse interactions, system behavioral models are difficult to develop early in system design and are challenging to maintain as designs are refined. This research develops methods to create, verify, and maintain multidisciplinary system models developed from models that are already part of system design. First, this research introduces a system model formulation that enables virtually any existing engineering model to become part of a large, trusted population of component models from which system behavioral models can be developed. Second, it creates a new algorithm to efficiently quantify the feasible domain over which the system model can be used. Finally, it quantifies system model accuracy early in system design before system measurements are available so that system models can be used to validate system design decisions. The results of this research are enabling system designers to evaluate the effects of design decisions early in system design, improving the predictability of the system design process, and enabling exploration of system designs that differ greatly from existing solutions.

In the current context of the energy transition, it has been argued by researchers and authors that the demand for raw materials for the necessary green technologies can’t be met without the input of primary raw materials. These materials can only be supplied through the mining cycle: exploration, mining, and processing. The mining cycle, however, can pose risks to the environment, which could be in contradiction with the motivation behind the implementation of green technologies. It is then society’s duty to strive for a constant reduction of the environmental impact of the mining cycle, or else, we would be in a paradoxical situation where, by mining materials to power the energy transition, if not done with care, we could be also risking the environment.  While this megatrend of the energy transition occurs, Unmanned Aerial Vehicles (UAVs) also known as drones, have reached a significant level of development which together with the miniaturization of geoscientific sensors, has opened the door to interesting fast, agile, and non-invasive ways of obtaining geological information. This has bridged gaps between the traditional scales of airborne and ground surveying and holds the potential of contributing to a less environmentally harmful mining cycle.  This thesis work intends to be a useful reference for anyone interested in working with UAVs in geosciences, especially for the exploration and management of raw materials from an entrepreneurial point of view. Here, a brief review of the current state of the art through the recent scientific literature on applications of drones in the mining cycle, including but not limited to geophysics and hyperspectral imaging is presented. Using this state of the art as a point of departure, semi-structured interviews with different stakeholders in the mining cycle were conducted to answer the research questions. The concept of value, ubiquitously present in the business research literature, was used to analyze the benefits that the use of UAVs can bring to the raw materials industry and the efforts to reduce its environmental footprint. The opportunities for entrepreneurs to be the conduit to deploy such benefits in society were also analyzed.  The work ends with a summary of the qualitative research findings, highlighting how drones constitute an optimization tool that can be used in all the stages of the mining cycle. Additionally, it highlights that UAV gravity and electromagnetic methods, together with better data processing software for hyperspectral imaging, are currently some of the most sought out and/or needed solutions by users.