Preston Victoria Lynn

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Preston
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Victoria Lynn
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Now showing 1 - 7 of 7
  • Thesis
    Adaptive sampling of transient environmental phenomena with autonomous mobile platforms
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2019-09) Preston, Victoria Lynn
    In the environmental and earth sciences, hypotheses about transient phenomena have been universally investigated by collecting physical sample materials and performing ex situ analysis. Although the gold standard, logistical challenges limit the overall efficacy: the number of samples are limited to what can be stored and transported, human experts must be able to safely access or directly observe the target site, and time in the field and subsequently the laboratory, increases overall campaign expense. As a result, the temporal detail and spatial diversity in the samples may fail to capture insightful structure of the phenomenon of interest. The development of in situ instrumentation allows for near real-time analysis of physical phenomenon through observational strategies (e.g., optical), and in combination with unmanned mobile platforms, has considerably impacted field operations in the sciences. In practice, mobile platforms are either remotely operated or perform guided, supervised autonomous missions specified as navigation between humanselected waypoints. Missions like these are useful for gaining insight about a particular target site, but can be sample-sparse in scientifically valuable regions, particularly in complex or transient distributions. A skilled human expert and pilot can dynamically adjust mission trajectories based on sensor information. Encoding their insight onto a vehicle to enable adaptive sampling behaviors can broadly increase the utility of mobile platforms in the sciences. This thesis presents three field campaigns conducted with a human-piloted marine surface vehicle, the ChemYak, to study the greenhouse gases methane (CH4) and carbon dioxide (CO2) in estuaries, rivers, and the open ocean. These studies illustrate the utility of mobile surface platforms for environmental research, and highlight key challenges of studying transient phenomenon. This thesis then formalizes the maximum seek-and-sample (MSS) adaptive sampling problem, which requires a mobile vehicle to efficiently find and densely sample from the most scientifically valuable region in an a priori unknown, dynamic environment. The PLUMES algorithm — Plume Localization under Uncertainty using Maximum-ValuE information and Search—is subsequently presented, which addresses the MSS problem and overcomes key technical challenges with planning in natural environments. Theoretical performance guarantees are derived for PLUMES, and empirical performance is demonstrated against canonical uniform search and state-of-the-art baselines in simulation and field trials. Ultimately, this thesis examines the challenges of autonomous informative sampling in the environmental and earth sciences. In order to create useful systems that perform diverse scientific objectives in natural environments, approaches from robotics planning, field design, Bayesian optimization, machine learning, and the sciences must be drawn together. PLUMES captures the breadth and depth required to solve a specific objective within adaptive sampling, and this work as a whole highlights the potential for mobile technologies to perform intelligent autonomous science in the future.
  • Dataset
    Discovering hydrothermalism from afar: in situ methane instrumentation and change-point detection for decision-making
    (Woods Hole Oceanographic Institution, 2022-10-06) Michel, Anna P. M. ; Wankel, Scott D. ; Preston, Victoria Lynn ; Flaspohler, Genevieve Elaine ; Kapit, Jason ; Pardis, William A. ; Youngs, Sarah ; Martocello, Donald E. ; Girguis, Peter R. ; Roy, Nicholas
    Seafloor hydrothermalism plays a critical role in fundamental interactions between geochemical and biological processes in the deep ocean. A significant number of hydrothermal vents are hypothesized to exist, but many of these remain undiscovered due in part to the difficulty of detecting hydrothermalism using standard sensors on rosettes towed in the water column or robotic platforms performing surveys. Here, we use in situ methane sensors to complement standard sensing technology for hydrothermalism discovery and compare sensing equipment on a towed rosette and autonomous underwater vehicle (AUV) during a 17 km long transect in the Northern Guaymas Basin. This transect spatially intersected with a known hydrothermally active venting site. These data show that methane signaled possible hydrothermal activity 1.5-3 km laterally (100-150m vertically) from a known vent. Methane as a signal for hydrothermalism performed similarly to standard turbidity sensors (plume detection 2.2-3.3 km from reference source), and more sensitively and clearly than temperature, salinity, and oxygen instruments which readily respond to physical mixing in background seawater. We additionally introduce change-point detection algorithms---streaming cross-correlation and regime identification---as a means of real-time hydrothermalism discovery and discuss related data monitoring technologies that could be used in planning, executing, and monitoring explorative surveys for hydrothermalism.
  • Article
    Discovering hydrothermalism from afar: In Situ methane instrumentation and change-point detection for decision-making
    (Frontiers Media, 2022-10-25) Preston, Victoria Lynn ; Flaspohler, Genevieve Elaine ; Kapit, Jason ; Pardis, William A. ; Youngs, Sarah ; Martocello, Donald E., III ; Roy, Nicholas ; Girguis, Peter R. ; Wankel, Scott ; Michel, Anna P. M.
    Seafloor hydrothermalism plays a critical role in fundamental interactions between geochemical and biological processes in the deep ocean. A significant number of hydrothermal vents are hypothesized to exist, but many of these remain undiscovered due in part to the difficulty of detecting hydrothermalism using standard sensors on rosettes towed in the water column or robotic platforms performing surveys. Here, we use in situ methane sensors to complement standard sensing technology for hydrothermalism discovery and compare sensors on a towed rosette and an autonomous underwater vehicle (AUV) during a 17 km long transect in the Northern Guaymas Basin in the Gulf of California. This transect spatially intersected with a known hydrothermally active venting site. These data show that methane signalled possible hydrothermal-activity 1.5–3 km laterally (100–150 m vertically) from a known vent. Methane as a signal for hydrothermalism performed similarly to standard turbidity sensors (plume detection 2.2–3.3 km from reference source), and more sensitively and clearly than temperature, salinity, and oxygen instruments which readily respond to physical mixing in background seawater. We additionally introduce change-point detection algorithms—streaming cross-correlation and regime identification—as a means of real-time hydrothermalism discovery and discuss related data supervision technologies that could be used in planning, executing, and monitoring explorative surveys for hydrothermalism.
  • Article
    Observations of shallow methane bubble emissions from Cascadia Margin
    (Frontiers Media, 2021-04-29) Michel, Anna P. M. ; Preston, Victoria Lynn ; Fauria, Kristen ; Nicholson, David P.
    Open questions exist about whether methane emitted from active seafloor seeps reaches the surface ocean to be subsequently ventilated to the atmosphere. Water depth variability, coupled with the transient nature of methane bubble plumes, adds complexity to examining these questions. Little data exist which trace methane transport from release at a seep into the water column. Here, we demonstrate a coupled technological approach for examining methane transport, combining multibeam sonar, a field-portable laser-based spectrometer, and the ChemYak, a robotic surface kayak, at two shallow (<75 m depth) seep sites on the Cascadia Margin. We demonstrate the presence of elevated methane (above the methane equilibration concentration with the atmosphere) throughout the water column. We observe areas of elevated dissolved methane at the surface, suggesting that at these shallow seep sites, methane is reaching the air-sea interface and is being emitted to the atmosphere.
  • Dataset
    Hunting Bubbles Falkor Cruise 2019
    (Woods Hole Oceanographic Institution, 2019-12-23) Michel, Anna P. M. ; Wankel, Scott D. ; Nicholson, David P. ; Fauria, Kristen ; Preston, Victoria Lynn
    The Hunting Bubbles Cruise took place in August-September 2018 on the R/V Falkor (cruise ID 180824). Ship time was provided by the Schmidt Ocean Institute. This cruise investigated transport of methane from seeps located on the Cascadia Margin. Data archived at the WHOAS repository supplements additional data from this cruise available at the R2R rolling deck to repository and at MGDS: Marine Geoscience Data System.
  • Thesis
    Perceive, predict, and plan: robotic expeditionary science in oceanic spatiotemporal fields
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2023-02) Preston, Victoria Lynn ; Roy, Nicholas ; Michel, Anna P. M.
    An improved understanding of our ocean would allow us to characterize the largest habitable biosphere on planet Earth, quantify the geochemical processes that control Earth’s climate, and develop responsible regulations for controlling the natural resources stored in its depths. Expeditionary science is the art of collecting in situ observations of an environment to build approximate models of underlying properties that move us towards this understanding. Robotic platforms are a critical technology for collecting observations of the ocean. Depth-capable autonomous underwater vehicles (AUVs) are commonly used to build static maps of the seafloor by executing pre-programmedsurveys. However, there is growing urgency to generate rich data products of spatiotemporal distributions that characterize the physics and chemistry of the deep ocean biogeosphere. In this thesis, the problem of charting dynamic deep sea hydrothermal plumes with depth-capable AUVs is investigated. Effectively collecting samples of geochemical plumes using the operationally preferred strategy of pre-specifying surveys requires access to a dynamics model of the advective currents, bathymetric updrafts, and turbulent mixing at a hydrothermal site. In practice, however, access to this information is unavailable, imperfect, or only partially known, and so a model of plume dynamics must be inferred from observations and subsequently leveraged to improve future sampling performance. As most in situ scientific instruments yield point-measurements, considerable uncertainty is placed over the form of the dynamics in purely data-driven solutions. Challenges related to planning under uncertainty for geochemical surveys in the deep ocean are addressed in this thesis by embedding scientific knowledge as a strong inductive prior for tractable model learning and decision-making. Algorithmic contributions of this thesis show how plumes can be perceived from field data, their fate predicted far into the future (e.g., multiple days), and informative fixed trajectories planned which place an AUV in the right place at the right time. Scientific assessment of observational data collected with AUV Sentry during field trials in the Guaymas Basin, Gulf of California are interwoven with algorithmic analyses, demonstrating how intelligent perception, prediction, and planning enables novel insights about hydrothermal plumes.
  • Article
    River Inflow Dominates Methane Emissions in an Arctic Coastal System
    (American Geophysical Union, 2020-04-23) Manning, Cara C. ; Preston, Victoria Lynn ; Jones, Samantha F. ; Michel, Anna P. M. ; Nicholson, David P. ; Duke, Patrick J. ; Ahmed, Mohamed M. M. ; Manganini, Kevin ; Else, Brent G. T. ; Tortell, Philippe D.
    We present a year‐round time series of dissolved methane (CH4), along with targeted observations during ice melt of CH4 and carbon dioxide (CO2) in a river and estuary adjacent to Cambridge Bay, Nunavut, Canada. During the freshet, CH4 concentrations in the river and ice‐covered estuary were up to 240,000% saturation and 19,000% saturation, respectively, but quickly dropped by >100‐fold following ice melt. Observations with a robotic kayak revealed that river‐derived CH4 and CO2 were transported to the estuary and rapidly ventilated to the atmosphere once ice cover retreated. We estimate that river discharge accounts for >95% of annual CH4 sea‐to‐air emissions from the estuary. These results demonstrate the importance of resolving seasonal dynamics in order to estimate greenhouse gas emissions from polar systems.