A Framework for Assessing Lower-Bound Bearing Capacity of Sandy Coastal Sediments from Remotely Sensed Imagery

dc.contributor.authorPaprocki, Julie Annaen
dc.contributor.committeechairStark, Ninaen
dc.contributor.committeememberGraber, Hans Christianen
dc.contributor.committeememberDove, Joseph E.en
dc.contributor.committeememberWadman, Heidi M.en
dc.contributor.committeememberRodriguez-Marek, Adrianen
dc.contributor.departmentCivil and Environmental Engineeringen
dc.date.accessioned2022-06-22T16:29:30Zen
dc.date.available2022-06-22T16:29:30Zen
dc.date.issued2022-04-28en
dc.description.abstractWith advances in modern technology, satellite-based data is rapidly becoming a viable option for geotechnical site characterization. Commercial satellite data offers high resolution (~25-200 cm), increased spatial coverage on the order of kilometers, short revisit times leading to high temporal coverage, and allows for data to be analyzed rapidly and remotely without the need for physical site access. These advantages are particularly attractive for characterizing coastal sites, where both the strength properties and moisture content can change rapidly in response to tidal stages, wave runup, and storm events. To date, there have been limited investigations into the use of satellite-based data for characterizing geotechnical properties of sandy beach sediments. Furthermore, the use of these moisture contents to estimate the soil strength of beaches has been limited. The goal of this research was to develop pathways to estimate the moisture content of sandy beach sites utilizing satellite-based data. For this study, both optical and synthetic aperture radar (SAR) images were collected at two sites: the Atlantic beach near the US Army Corps of Engineers Field Research Facility in Duck, North Carolina and three distinct sites located near Yakutat, Alaska (Cannon Beach, Ocean Cape, and Point Carrew). During satellite overflight, ground measurements of moisture content, grain size, unit weight, porosity, and bearing capacity were collected. Using the field measurements, this research (1) developed a framework to estimate the moisture content of sandy beach sediments from satellite-based optical images; (2) investigated the necessary collection parameters to estimate the moisture content from SAR images; and (3) developed a framework to estimate the bearing capacity of sandy beaches using moisture contents derived from satellite-based images. The results of this study demonstrated that optical images can produce reasonable estimates of the moisture content when compared to field measurements and are strongly influenced by local morphology. Additionally, SAR images with incidence angles of 30°-50° produced the best results when compared to field measurements. Finally, using the spatial estimates moisture content produced from satellite data and standard sediment, maps of bearing capacity can be developed to predict beach trafficability.en
dc.description.abstractgeneralThe strength of sandy beaches is impacted by the density, particle size and shape, distribution of grain sizes, mineralogy, and moisture content. For coastal sites, which typically have a dominant mineralogy and a limited range of grain sizes, a main factor changing is the moisture content. This varying moisture content can result in the increase or decrease in soil strength, and impacts modelling for coastal challenges such as erosion or beach trafficability (i.e., the ability to drive on the beach) on large scales. It is common to measure moisture content through sampling or moisture probes, but these represent point measurements and may not accurately capture the spatial and temporal moisture contents at a beach. Recently, satellite-based images have become popular for assessing processes and environmental changes over large areas. However, their use for mapping moisture content at sandy beaches has been limited, and the proper models are unknown. As such, the goal of this research is to investigate the use of satellite images to map moisture content over large areas. For this study, measurements were conducted at two sites: an Atlantic beach located near the US Army Corps of Engineers Field Research Facility in Duck, North Carolina and three distinct sites located near Yakutat, Alaska (Cannon Beach, Ocean Cape, and Point Carrew). Simultaneously with ground measurements, two different types of images were collected. The first, optical data, collects data over the visible (400-700 nm) and near infrared (700-1300 nm) regions of the electromagnetic spectrum. These satellites use the sun to light the scene and the amount of energy reflected back to the satellite is used to estimate the moisture content. The second, X-band synthetic aperture radar (SAR) data (wavelengths of 3.1 cm), sends its own energy source to the ground and uses the returned energy to estimate the moisture content. Both optical and SAR are able to produce reasonable estimates of moisture content when compared to field measurements. These estimated values of moisture content are then tested in a model to estimate the sand strength, with those estimated values also following the expected trends. Ultimately, this work can be used to contribute to understanding how moisture content varies at sandy beaches and improve trafficability predictions in sandy beach environments.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:34288en
dc.identifier.urihttp://hdl.handle.net/10919/110870en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectSatellite imagesen
dc.subjectsite characterizationen
dc.subjectmoisture contenten
dc.subjectsand beachen
dc.subjectbearing capacityen
dc.subjectbeach trafficabilityen
dc.titleA Framework for Assessing Lower-Bound Bearing Capacity of Sandy Coastal Sediments from Remotely Sensed Imageryen
dc.typeDissertationen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

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