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dc.contributor.advisorBostater, Charles R.
dc.contributor.authorOney, Taylor Scott 2017
dc.descriptionThesis (M.S.) - Florida Institute of Technology, 2017en_US
dc.description.abstractHyperspectral measurements of the water surface in urban coastal waters are presented. Oblique bidirectional reflectance factor (BRF) imagery was acquired of coastal shallow waters within the watershed of the Indian River Lagoon, Florida and along littoral zone waters of the nearby Atlantic Ocean. Oblique imagery of the shoreline and subsurface features clearly shows subsurface bottom features and rip current features within the surf zone water column. The imagery was collected using a pushbroom hyperspectral imager mounted on a fixed platform with a calibrated circular mechatronic rotation stage. Hyperspectral imaging using the fixed platform techniques were used to calculate hyperspectral bidirectional reflectance factor (BRF) signatures from locations at buildings and bridges in order to provide new opportunities to advance the scientific understanding of aquatic environments in urbanized regions. (Bostater & Oney, 2016). A method was tested to correct the increase in reflectance due to increased surface area of pixels at off nadir viewing angles that is inherent in high oblique hyperspectral imagery. The hyperspectral image reflectance channels were corrected using a Lambertian grey panel and cross-calibrated to an SE590 solid state, high sensitivity spectrograph. The hyperspectral reflectance imagery was transposed from high oblique viewing geometry to nadir viewing image using calculated (a) ground control points (GCPs) selected at known distances, (b) spatially varying pixel sizes (GSD) from the imaging system, and (c) anisotropic signatures. The imagery was then tested for constituent detection such as dissolved organic matter (DOM), seston, and chlorophyll using a second derivative estimator described by Bostater, 1996.en_US
dc.rightsCC BY 4.0en_US
dc.titleNovel Hyperspectral Imagery and Platforms for Shallow Water Environmentsen_US
dc.typeThesisen_US of Science in Earth Remote Sensingen_US Remote Sensingen_US and Environmental Systemsen_US Institute of Technologyen_US

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