Date of Award
Fall 2024
Project Type
Thesis
Program or Major
Civil and Environmental Engineering
Degree Name
Master of Science
First Advisor
Julie Paprocki
Second Advisor
Majid Ghayoomi
Third Advisor
Fei Han
Abstract
Coastlines around the world are composed of a wide range of sediments. The classification of coastal soil ranges from coarse-grained sediments (gravels and sands, 75 mm to 0.075 mm), to fine-grained sediments (silts and clays, 0.075 mm and smaller). In geotechnical engineering applications, the shear strength of soil is a key characteristic and is commonly influenced by the classification, grain size, and water content of the soil. While site-specific investigation is the best method for obtaining these parameters, information regarding soil type can often be readily accessed from existing literature as a general classification. However, soil type can vary at a given site due to local site morphology and hydrodynamic conditions. To obtain preferable strength parameters, a more detailed analysis of soil type is often required. A potential solution is to use remotely sensed satellite-based imagery. Particularly, synthetic aperture radar (SAR) data is attractive, as it can collect data at night and through cloud coverage. SAR images are composed of the returned radar backscatter signal; for bare soils, backscatter is related to the water content and surface roughness, which can be related to soil type. In this paper, the potential of data obtained from satellite systems to classify soil types will be explored. Images were obtained from the publicly available C-band Sentinel-1 satellite (resolutions of ~10 m). Here, the backscatter will be used to analyze various soil types at multiples locations on the Great Bay Estuary in New Hampshire. Three separate tidal flats (two predominately fine soils, one predominately coast soils) were studied, each with varying soil properties. Results suggest that SAR backscatter from both satellites can be used to broadly differentiate between coarse- and fine-grained sediments.
Recommended Citation
Priest, Tess, "Assessment of Synthetic Aperture Radar for Classification of Exposed Coastal Soils in the Great Bay Estuary" (2024). Master's Theses and Capstones. 1896.
https://scholars.unh.edu/thesis/1896