| Summary: | With 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 ...
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