Modern prosumer small unmanned aircraft systems (sUAS) have eliminated many historical barriers to aerial remote sensing and photogrammetric survey data generation. The relatively low cost and operational ease of these platforms has driven their adoption for numerous geospatial applications including professional surveying and mapping. However, significant debate exists among geospatial professionals and academics regarding prosumer sUAS ability to achieve “survey-grade” geospatial accuracy ≤ 0.164 ft. in their derivative survey data. To address this debate, a controlled accuracy test experiment was conducted in accordance with federal standards whereby prosumer sUAS geospatial accuracies were reported between 15.367 ft. – 0.09 ft. horizontally and 496.734 ft. – 0.330 ft. vertically at the 95% confidence level. These results suggest prosumer sUAS derived survey data fall short of “survey-grade” accuracy in this experiment. Therefore, traditional surveying instruments and methods should not be relinquished in favor of prosumer sUAS for complex applications requiring “survey-grade” accuracy at this time.

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The focus of this dissertation is on developing novel methods and extending existing ones to improve the security and reliability of fixed-wing unmanned aircraft systems (UAS). Specifically, we focus on three strands of work: i) designing UAS controllers with performance guarantees using the robust control framework, ii) developing tools for detection and mitigation of physical-layer security threats in UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS. Under the first category, we use the robust H-infinity control approach to design a linear parameter-varying (LPV) path-following controller for a fixed-wing UAS that enables the aircraft to follow any arbitrary planar curvature-bounded path under significant environmental disturbances. Three other typical path-following controllers, namely, a linear time-invariant H-infinity controller, a nonlinear rate-tracking controller, and a PID controller, are also designed. We study the relative merits and limitations of each approach and demonstrate through extensive simulations and flight tests that the LPV controller has the most consistent position tracking performance for a wide array of geometric paths. Next, convex synthesis conditions are developed for control of distributed systems with uncertain initial conditions, whereby independent norm constraints are placed on the disturbance input and the uncertain initial state. Using this approach, we design a distributed controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories. Pertaining to the second strand of this dissertation, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, a probabilistic framework that employs tools from statistical analysis to detect sensor attacks on UAS is proposed. By incorporating knowledge about the physical system and using a Bayesian network, the proposed approach minimizes the false alarm rates, which is a major challenge for UAS that operate in dynamic and uncertain environments. Next, the security vulnerabilities of existing UAS actuators are identified and three different methods of differing complexity and effectiveness are proposed to detect and mitigate the security threats. While two of these methods involve developing algorithms and do not require any hardware modification, the third method entails hardware modifications to the actuators to make them resilient to malicious attacks. The three methods are compared in terms of different attributes such as computational demand and detection latency. As for the third strand of this dissertation, tools from formal methods such as compositional verification are used to design an unmanned multi-aircraft system that is deployed in a geofencing application, where the design objective is to guarantee a critical global system property. Verifying such a property for the multi-aircraft system using monolithic (system-level) verification techniques is a challenging task due to the complexity of the components and the interactions among them. To overcome these challenges, we design the components of the multi-aircraft system to have a modular architecture, thereby enabling the use of component-based reasoning to simplify the task of verifying the global system property. For component properties that can be formally verified, we employ results from Euclidean geometry and formal methods to prove those properties. For properties that are difficult to be formally verified, we rely on Monte Carlo simulations. We demonstrate how compositional reasoning is effective in reducing the use of simulations/tests needed in the verification process, thereby increasing the reliability of the unmanned multi-aircraft system. / Doctor of Philosophy / Given the safety-critical nature of many unmanned aircraft systems (UAS), it is crucial for stake holders to ensure that UAS when deployed behave as intended despite atmospheric disturbances, system uncertainties, and malicious adversaries. To this end, this dissertation deals with developing novel methods and extending existing ones to improve the security and reliability of fixed-wing UAS. Specifically, we focus on three key areas: i) designing UAS controllers with performance guarantees, ii) developing tools for detection and mitigation of security threats to sensors and actuators of UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS. Pertaining to the first area, we design controllers for UAS that would enable the aircraft to follow any arbitrary planar curvature-bounded path under significant atmospheric disturbances. Four different controllers of differing complexity and effectiveness are designed, and their relative merits and limitations are demonstrated through extensive simulations and flight tests. Next, we develop control design tools to improve the transient response of multi-mission UAS networks. Using these tools, we design a controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories. As for the contributions in the second area, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, we propose a framework for detecting sensor attacks on UAS. By judiciously using knowledge about the physical system and techniques from statistical analysis, the framework minimizes the false alarm rates, which is a major challenge in designing attack detection systems for UAS. Then, we focus on another important attack surface of the UAS, namely, the actuators. Here, we identify the security vulnerabilities of existing UAS actuators and propose three different methods to detect and mitigate the security threats. The three methods are compared in terms of different attributes such as computational demand, detection latency, need for hardware modifications, etc. In regard to the contributions in the third area, tools from compositional verification are used to design an unmanned multi-aircraft system that is tasked to track and compromise an aerial encroacher, wherein the multi-aircraft system is required to satisfy a global system property pertaining to collision avoidance and close tracking. A common approach to verifying global properties of systems is monolithic verification where the whole system is analyzed. However, such an approach becomes intractable for complex systems like the multi-aircraft system considered in this work. We overcome this difficulty by employing the compositional verification approach, whereby the problem of verifying the global system property is reduced to a problem of reasoning about the system’s components. That being said, even formally verifying some component properties can be a formidable task; in such cases, one has to rely on Monte Carlo simulations. By suitably designing the components of the multi-aircraft system to have a modular architecture, we show how one can perform focused component-level simulations rather than conduct simulations on the whole system, thereby limiting the use of simulations during the verification process and, as a result, increasing the reliability of the system.

The main contributions of this work are applications of robust control and analysis methods to complex engineering systems, namely, small fixed-wing unmanned aircraft systems (UAS). Multiple path-following controllers for a small fixed-wing Telemaster UAS are presented, including a linear parameter-varying (LPV) controller scheduled over path curvature. The controllers are synthesized based on a lumped path-following and UAS dynamic system, effectively combining the six degree-of-freedom aircraft dynamics with established parallel transport frame virtual vehicle dynamics. The robustness and performance of these controllers are tested in a rigorous MATLAB simulation environment that includes steady winds, turbulence, measurement noise, and delays. After being synthesized off-line, the controllers allow the aircraft to follow prescribed geometrically defined paths bounded by a maximum curvature. The controllers presented within are found to be robust to the disturbances and uncertainties in the simulation environment. A robust analysis framework for mathematical validation of flight control systems is also presented. The framework is specifically developed for the complete uncertainty characterization, quantification, and analysis of small fixed-wing UAS. The analytical approach presented within is based on integral quadratic constraint (IQC) analysis methods and uses linear fractional transformations (LFTs) on uncertainties to represent system models. The IQC approach can handle a wide range of uncertainties, including static and dynamic, linear time-invariant and linear time-varying perturbations. While IQC-based uncertainty analysis has a sound theoretical foundation, it has thus far mostly been applied to academic examples, and there are major challenges when it comes to applying this approach to complex engineering systems, such as UAS. The difficulty mainly lies in appropriately characterizing and quantifying the uncertainties such that the resulting uncertain model is representative of the physical system without being overly conservative, and the associated computational problem is tractable. These challenges are addressed by applying IQC-based analysis tools to analyze the robustness of the Telemaster UAS flight control system. Specifically, uncertainties are characterized and quantified based on mathematical models and flight test data obtained in house for the Telemaster platform and custom autopilot. IQC-based analysis is performed on several time-invariant H∞ controllers along with various sets of uncertainties aimed at providing valuable information for use in controller analysis, controller synthesis, and comparison of multiple controllers. The proposed framework is also transferable to other fixed-wing UAS platforms, effectively taking IQC-based analysis beyond academic examples to practical application in UAS control design and airworthiness certification. IQC-based analysis problems are traditionally solved using convex optimization techniques, which can be slow and memory intensive for large problems. An oracle for discrete-time IQC analysis problems is presented to facilitate the use of a cutting plane algorithm in lieu of convex optimization in order to solve large uncertainty analysis problems relatively quickly, and with reasonable computational effort. The oracle is reformulated to a skew-Hamiltonian/Hamiltonian eigenvalue problem in order to improve the robustness of eigenvalue calculations by eliminating unnecessary matrix multiplications and inverses. Furthermore, fast, structure exploiting eigensolvers can be employed with the skew-Hamiltonian/Hamiltonian oracle to accurately determine critical frequencies when solving IQC problems. Applicable solution algorithms utilizing the IQC oracle are briefly presented, and an example shows that these algorithms can solve large problems significantly faster than convex optimization techniques. Finally, a large complex engineering system is analyzed using the oracle and a cutting-plane algorithm. Analysis of the same system using the same computer hardware failed when employing convex optimization techniques. / Ph. D.

The theory of Lagrangian Coherent Structures (LCS) enables prediction of material transport by turbulent winds, such as those observed in the Earth's Atmospheric Boundary Layer. In this dissertation, both theory and experimental methods are developed for utilizing small fixed-wing unmanned aircraft systems (UAS) in detecting these atmospheric coherent structures. The dissertation begins by presenting relevant literature on both LCS and airborne wind estimation. Because model-based wind estimation inherently depends on high quality models, a Flight Dynamic Model (FDM) suitable for a small fixed-wing aircraft in turbulent wind is derived in detail. In this presentation, some new theoretical concepts are introduced concerning the proper treatment of spatial wind gradients, and a critical review of existing theories is presented. To enable model-based wind estimation experiments, an experimental approach is detailed for identifying a FDM for a small UAS by combining existing computational aerodynamic and data-driven approaches. Additionally, a methodology for determining wind estimation error directly resulting from dynamic modeling choices is presented and demonstrated. Next, some model-based wind estimation results are presented utilizing the experimentally identified FDM, accompanied by a discussion of model fidelity concerns and other experimental issues. Finally, an algorithm for detecting LCS from a single circling fixed-wing UAS is developed and demonstrated in an Observing System Simulation Experiment. The dissertation concludes by summarizing these contributions and recommending future paths for continuing research. / Doctor of Philosophy / In a natural or man-made disaster, first responders depend on accurate predictions of where the wind might carry hazardous material. A mathematical theory of Lagrangian Coherent Structures (LCS) has shown promise in ocean environments to improve these predictions, and the theory is also applicable to atmospheric flows near the Earth’s surface. This dissertation presents both theoretical and experimental research efforts towards employing small fixed-wing unmanned aircraft systems (UAS) to detect coherent structures in the Atmospheric Boundary Layer (ABL). These UAS fit several “gaps” in available sensing technology: a small aircraft responds significantly to wind gusts, can be steered to regions of interest, and can be flown in dangerous environments without risking the pilot’s safety. A key focus of this dissertation is to improve the quality of airborne wind measurements provided by inexpensive UAS, specifically by leveraging mathematical models of the aircraft. The dissertation opens by presenting the motivation for this research and existing literature on the topics. Next, a detailed derivation of a suitable Flight Dynamic Model (FDM) for a fixed-wing aircraft in a turbulent wind field is presented. Special attention is paid to the theories for including aerodynamic effects of flying in non-uniform winds. In preparation for wind measurement experiments, a practical method for obtaining better quality FDMs is presented which combines theoretically based and data-driven approaches. A study into the wind-measurement error incurred solely by mathematical modeling is presented, focusing on simplified forms of the FDM which are common in aerospace engineering. Wind estimates which utilize our best available model are presented, accompanied by discussions of the model accuracy and additional wind measurement concerns. A method is developed to detect coherent structures from a circling UAS which is providing wind information, presumably via accurate model based estimation. The dissertation concludes by discussing these conclusions and directions for future research which have been identified during these pursuits.

In the past few years, there has been a growth in Unmanned Aircraft Systems (UAS) numbers in segregated airspace. However, although there is an interest in integrating large UAS into non-segregated airspace, the safety challenges on its integration arise from the inclusion of new ways of reaching unsafe states into the airspace. Furthermore, Air Traffic Controllers (ATCo) aim to o?er appropriate levels of safety and efficiency and to solve issues present in complex situations. Although the UAS technology may be used in di?erent situations and brings several advantages to the airspace (e.g. efficiency), it may bring uncertainties due to the fact that ATCos may not be familiar with them. Throughout the years, this impact may be lower then it is nowadays due to the fact that the present lack of familiarity in the relationship between UAS and ATCo contributes to higher workload levels. Furthermore, Terminal Maneuvering Area (TMA), which composes the controlled airspace and in which the final sector in contained, is a critical control area normally established at the confluence of Air Traffic Service (ATS) routes in which the aircraft tend to be closer to each other. Thus, operations in this particular area are conducted carefully and, in order to achieve desirable levels of safety and efficiency, standard procedures are established. In some cases, however, standard procedures cannot be followed and the sequencing of the aircraft during the approach, which is a highly challenging task due to complex maneuvers constraints, must be performed by the ATCo in a manner to respect the minimum separation of aircraft and to avoid flights through cumulonimbus (CB). Finally, the main goal of defining a final arrival segment is to deliver the set of aircraft from the final sector of the TMA to the final phase of its landing procedure, i.e., the final approach, considering the operation efficiency and safety. The main objective of this research is to propose a parallel swarm-based method for optimizing final aircraft arrival segments design, i.e., routes that connects the final sector to the Initial Approach Fix (IAF), considering the UAS presence. This is conducted from two perspectives: ATCo workload, which is related to safety, and sequencing duration, which is related to efficiency. Furthermore, di?erent phases of UAS integration are considered, i.e., from early stages of its integration to a mature stage of its operation by means of the Technology Maturity Level (TML) usage, which is a scale that measure the familiarity between the ATCo with the aircraft. Finally, the solutions consider airspace restrictions such as minimum separation between aircraft and bad weather conditions, i.e., the presence of cumulonimbus (CB). The experiments conducted show that this approach is able to build safe and efficient solution even in situations with a high number of aircraft. / Nos últimos anos, houve um crescimento, no espaço aéreo segregado, nos números do Veículos Aéreos Não-Tripulados (VANT). No entanto, embora exista interesse em integrar grandes VANT em espaço aéreo não-segregado, os desafios de segurança decorrem da inclusão de novas formas de alcançar estados inseguros no espaço aéreo (ATCo) tem como objetivo oferecer níveis adequados de segurança e eficiência e resolver problemas presentes em situações complexas. Embora VANTs possam ser usados em diferentes situações e trazem várias vantagens para o espaço aéreo (por exemplo, eficiência), podem trazer incertezas devido ao fato de que os ATCos não estão familiarizados com essa tecnologia. Ao longo dos anos, esse impacto pode ser menor, e atualmente a falta de familiaridade na relação entre VANT e ATCo contribui para níveis mais altos de carga de trabalho. Além disso, a Área Terminal (TMA), que compõe o espaço aéreo controlado, é uma área de controle crítico normalmente estabelecida na confluência de rotas do Servi¸co de Tráfego Aéreo (ATS), nas quais as aeronaves tendem a estar mais próximas umas das outras. Assim, as operações nesta área particular são realizadas com cuidado e, para alcançar níveis desejáveis de segurança e eficiência, os procedimentos padrão são estabelecidos. Em alguns casos, no entanto, procedimentos padrão não podem ser seguidos e o sequenciamento da aeronave durante a aproximação, que é uma tarefa desafiadora por conta das restrições de manobras complexas, deve ser realizada pelo ATCo de forma a garantir separação mínima entre aeronaves e evitar voos através de cumulonimbus (CB). Finalmente, o principal objetivo de definir um segmento de chegada final ´e entregar o conjunto de aeronaves do setor final, da TMA, para a fase final do seu procedimento de pouso, ou seja, a aproximação final, considerando a eficiência e a segurança da operação. O objetivo desta pesquisa é propor um método paralelo baseado em enxame para otimizar o projeto final de segmentos de chegada de aeronaves, ou seja, rotas que conectem o setor final com o Fixo de Aproximação Inicial (IAF), considerando a presença de VANTs. Esse processo ´e conduzido a partir de duas perspectivas: a carga de trabalho do ATCo, que est´a relacionada à segurança, e a duração da sequenciamento, que está relacionado à eficiência. Além disso, são consideradas diferentes fases da integração de VANTs, ou seja, desde os primeiros estágios de sua integra¸c~ao at´e um estágio maduro de sua operação por meio do uso do Nível de Maturidade Tecnológica (TML), que é uma escala que mede a familiaridade entre o ATCo e a aeronave. Finalmente, as soluções consideram as restrições do espaço aéreo, como a separação mínima entre aeronaves e condições climáticas adversas, isto é, a presença de cumulonimbus (CB). Os experimentos realizados mostram que essa abordagem é capaz de criar soluções seguras e eficientes mesmo em situações com um grande número de aeronaves.

<p></p><p>Visual inspection is the primary means of ensuring the safety and functionality of in-service bridges in the United States and owners spend considerable resources on such inspections. While the Federal Highway Administration (FHWA) and many state departments of transportation have guidelines related to inspector qualification, training, and certification, an inspector’s actual capability to identify defects in the field under these guidelines is unknown. This research aimed to address the knowledge gap surrounding visual inspection performance for steel bridges in order to support future advances in inspection and design procedures. Focusing primarily on fatigue crack detection, this research also considered the ability of inspectors to accurately and consistently estimate section loss in steel bridge members. </p> <p> </p> <p>Inspection performance was evaluated through a series of simulated bridge inspections performed in representative in-situ conditions. First, this research describes the results from 30 hands-on, visual inspections performed on full size bridge specimens with known fatigue cracks. Probability of Detection (POD) curves were fit to the inspection results and the 50% and 90% detection rate crack lengths were determined. The variability in performance was large, and only a small amount of the variance could be explained by individual characteristics or environmental conditions. Based on the results, recommendations for improved training methods, inspection procedures, and equipment were developed. Above all, establishment of a performance based qualification system for bridge inspectors is recommended to confirm that a satisfactory level of performance is consistently achieved in the field. </p> <p> </p> <p>Long term, managing agencies may eschew traditional hands-on bridge inspection methods in favor of emerging technologies imagined to provide improved results and fewer logistical challenges. This research investigated the potential for unmanned aircraft system (UAS) assistance during visual inspection of steel bridges. Using the same specimens as in the hands-on inspections, four UAS-assisted field inspections and 19 UAS-assisted desk inspections were performed. A direct comparison was made between performance in the hands-on and UAS-assisted inspections, as well as between performance in the two types of UAS-assisted inspections. Again, significant variability was present in the results suggesting that human factors continue to have a substantial influence on inspection performance, regardless of inspection method. </p> <p> </p> <p>Finally, to expand the findings from the crack detection inspections, the lower chord from a deck truss was used to investigate variability in the inspection of severely corroded steel tension members. Five inspectors performed a hands-on inspection of the specimen and four engineers calculated the load rating for the same specimen. Significant variability was observed in how inspectors recorded thickness measurements during the inspections and engineers interpreted the inspection reports and applied the code requirements. </p><br><p></p>

In the past few years, there has been a growth in Unmanned Aircraft Systems (UAS) numbers in segregated airspace. However, although there is an interest in integrating large UAS into non-segregated airspace, the safety challenges on its integration arise from the inclusion of new ways of reaching unsafe states into the airspace. Furthermore, Air Traffic Controllers (ATCo) aim to o?er appropriate levels of safety and efficiency and to solve issues present in complex situations. Although the UAS technology may be used in di?erent situations and brings several advantages to the airspace (e.g. efficiency), it may bring uncertainties due to the fact that ATCos may not be familiar with them. Throughout the years, this impact may be lower then it is nowadays due to the fact that the present lack of familiarity in the relationship between UAS and ATCo contributes to higher workload levels. Furthermore, Terminal Maneuvering Area (TMA), which composes the controlled airspace and in which the final sector in contained, is a critical control area normally established at the confluence of Air Traffic Service (ATS) routes in which the aircraft tend to be closer to each other. Thus, operations in this particular area are conducted carefully and, in order to achieve desirable levels of safety and efficiency, standard procedures are established. In some cases, however, standard procedures cannot be followed and the sequencing of the aircraft during the approach, which is a highly challenging task due to complex maneuvers constraints, must be performed by the ATCo in a manner to respect the minimum separation of aircraft and to avoid flights through cumulonimbus (CB). Finally, the main goal of defining a final arrival segment is to deliver the set of aircraft from the final sector of the TMA to the final phase of its landing procedure, i.e., the final approach, considering the operation efficiency and safety. The main objective of this research is to propose a parallel swarm-based method for optimizing final aircraft arrival segments design, i.e., routes that connects the final sector to the Initial Approach Fix (IAF), considering the UAS presence. This is conducted from two perspectives: ATCo workload, which is related to safety, and sequencing duration, which is related to efficiency. Furthermore, di?erent phases of UAS integration are considered, i.e., from early stages of its integration to a mature stage of its operation by means of the Technology Maturity Level (TML) usage, which is a scale that measure the familiarity between the ATCo with the aircraft. Finally, the solutions consider airspace restrictions such as minimum separation between aircraft and bad weather conditions, i.e., the presence of cumulonimbus (CB). The experiments conducted show that this approach is able to build safe and efficient solution even in situations with a high number of aircraft. / Nos últimos anos, houve um crescimento, no espaço aéreo segregado, nos números do Veículos Aéreos Não-Tripulados (VANT). No entanto, embora exista interesse em integrar grandes VANT em espaço aéreo não-segregado, os desafios de segurança decorrem da inclusão de novas formas de alcançar estados inseguros no espaço aéreo (ATCo) tem como objetivo oferecer níveis adequados de segurança e eficiência e resolver problemas presentes em situações complexas. Embora VANTs possam ser usados em diferentes situações e trazem várias vantagens para o espaço aéreo (por exemplo, eficiência), podem trazer incertezas devido ao fato de que os ATCos não estão familiarizados com essa tecnologia. Ao longo dos anos, esse impacto pode ser menor, e atualmente a falta de familiaridade na relação entre VANT e ATCo contribui para níveis mais altos de carga de trabalho. Além disso, a Área Terminal (TMA), que compõe o espaço aéreo controlado, é uma área de controle crítico normalmente estabelecida na confluência de rotas do Servi¸co de Tráfego Aéreo (ATS), nas quais as aeronaves tendem a estar mais próximas umas das outras. Assim, as operações nesta área particular são realizadas com cuidado e, para alcançar níveis desejáveis de segurança e eficiência, os procedimentos padrão são estabelecidos. Em alguns casos, no entanto, procedimentos padrão não podem ser seguidos e o sequenciamento da aeronave durante a aproximação, que é uma tarefa desafiadora por conta das restrições de manobras complexas, deve ser realizada pelo ATCo de forma a garantir separação mínima entre aeronaves e evitar voos através de cumulonimbus (CB). Finalmente, o principal objetivo de definir um segmento de chegada final ´e entregar o conjunto de aeronaves do setor final, da TMA, para a fase final do seu procedimento de pouso, ou seja, a aproximação final, considerando a eficiência e a segurança da operação. O objetivo desta pesquisa é propor um método paralelo baseado em enxame para otimizar o projeto final de segmentos de chegada de aeronaves, ou seja, rotas que conectem o setor final com o Fixo de Aproximação Inicial (IAF), considerando a presença de VANTs. Esse processo ´e conduzido a partir de duas perspectivas: a carga de trabalho do ATCo, que est´a relacionada à segurança, e a duração da sequenciamento, que está relacionado à eficiência. Além disso, são consideradas diferentes fases da integração de VANTs, ou seja, desde os primeiros estágios de sua integra¸c~ao at´e um estágio maduro de sua operação por meio do uso do Nível de Maturidade Tecnológica (TML), que é uma escala que mede a familiaridade entre o ATCo e a aeronave. Finalmente, as soluções consideram as restrições do espaço aéreo, como a separação mínima entre aeronaves e condições climáticas adversas, isto é, a presença de cumulonimbus (CB). Os experimentos realizados mostram que essa abordagem é capaz de criar soluções seguras e eficientes mesmo em situações com um grande número de aeronaves.

Excessive erosion and fine sediment delivery to river corridors and receiving waters degrade aquatic habitat, add to nutrient loading, and impact infrastructure. Understanding the sources and movement of sediment within watersheds is critical for assessing ecosystem health and developing management plans to protect natural and human systems. As our changing climate continues to cause shifts in hydrological regimes (e.g., increased precipitation and streamflow in the northeast U.S.), the development of tools to better understand sediment dynamics takes on even greater importance. In this research, advanced geomatics and machine learning are applied to improve the (1) monitoring of streambank erosion, (2) understanding of event sediment dynamics, and (3) prediction of sediment loading using meteorological data as inputs. Streambank movement is an integral part of geomorphic changes along river corridors and also a significant source of fine sediment to receiving waters. Advances in unmanned aircraft systems (UAS) and photogrammetry provide opportunities for rapid and economical quantification of streambank erosion and deposition at variable scales. We assess the performance of UAS-based photogrammetry to capture streambank topography and quantify bank movement. UAS data were compared to terrestrial laser scanner (TLS) and GPS surveying from Vermont streambank sites that featured a variety of bank conditions and vegetation. Cross-sectional analysis of UAS and TLS data revealed that the UAS reliably captured the bank surface and was able to quantify the net change in bank area where movement occurred. Although it was necessary to consider overhanging bank profiles and vegetation, UAS-based photogrammetry showed significant promise for capturing bank topography and movement at fine resolutions in a flexible and efficient manner. This study also used a new machine-learning tool to improve the analysis of sediment dynamics using three years of high-resolution suspended sediment data collected in the Mad River watershed. A restricted Boltzmann machine (RBM), a type of artificial neural network (ANN), was used to classify individual storm events based on the visual hysteresis patterns present in the suspended sediment-discharge data. The work expanded the classification scheme typically used for hysteresis analysis. The results provided insights into the connectivity and sources of sediment within the Mad River watershed and its tributaries. A recurrent counterpropagation network (rCPN) was also developed to predict suspended sediment discharge at ungauged locations using only local meteorological data as inputs. The rCPN captured the nonlinear relationships between meteorological data and suspended sediment discharge, and outperformed the traditional sediment rating curve approach. The combination of machine-learning tools for analyzing storm-event dynamics and estimating loading at ungauged locations in a river network provides a robust method for estimating sediment production from catchments that informs watershed management.

Small unmanned aircraft systems (UAS) are rapidly gaining popularity. As the excitement surrounding small UAS has grown, the Federal Aviation Administration (FAA) has repeatedly stated that UAS must be capable of detecting and avoiding manned and unmanned aircraft. In developing detect-and-avoid (DAA) technology, one of the key challenges is identifying a suitable sensor. Automatic Dependent Surveillance-Broadcast (ADS-B) has gained much attention in both the research and consumer sectors as a promising solution. While ADS-B has many positive characteristics, further analysis is necessary to determine if it is suitable as a DAA sensor in environments with high-density small UAS operations. To further the understanding of ADS-B, we present a characterization of ADS-B measurement error that is derived from FAA regulations. Additionally, we analyze ADS-B by examining its strengths and weaknesses from the perspective of DAA on small UAS. To demonstrate the need and method for estimation of ADS-B measurements, we compare four dynamic filters for accuracy and computational speed. The result of the comparison is a recommendation for the best filter for ADS-B estimation. We then demonstrate this filter by estimating ADS-B measurements that have been recorded from the National Airspace System (NAS). We also present a novel long-range, convex optimization-based path planner for ADS-B-equipped small UAS in the presence of intruder aircraft. This optimizer is tested using a twelve-state simulation of the ownship and intruders.We also consider the effectiveness of ADS-B in high-density airspace. To do this we present a novel derivation of the probability of interference for ADS-B based on the number of transmitting aircraft. We then use this probability to document the need for limited transmit range for ADS-B on small UAS. We further leverage the probability of interference for ADS-B, by creating a tool that can be used to analyze self-separation threshold (SST) and well clear (WC) definitions based on ADS-B bandwidth limitations. This tool is then demonstrated by evaluating current SST and WC definitions and making regulations recommendations based on the analysis. Coupling this tool with minimum detection range equations, we make a recommendation for well clear for small UAS in ADS-B congested airspace. Overall these contributions expand the understanding of ADS-B as a DAA sensor, provide viable solutions for known and previously unknown ADS-B challenges, and advance the state of the art for small UAS.