Graduation Year
2005
Document Type
Thesis
Degree
M.S.
Degree Granting Department
Marine Science
Major Professor
Kendall L. Carder, Ph.D.
Committee Member
Pamela Hallock Muller, Ph.D.
Committee Member
Gabriel Vargo, Ph.D.
Keywords
Ocean, Optics, Albedo, Sand, Seagrass
Abstract
Remote sensing reflectance data collected with a remotely operated vehicle (ROV) were used to derive bottom albedo and optical properties for a shallow marine environment near Lee Stocking Island, Bahamas. Optical model inversion techniques were applied to hyperspectral measurements of remote-sensing reflectance to derive water absorption and backscatter coefficients. Using these derived water properties, path attenuation and radiance effects were removed from bottom observations to derive bottom albedos. Histograms from multispectral, hyperspatial video images were used to determine the albedo range of optical end members observed in scenes of sand and seagrass. Variations of spectral signatures for optical end members caused by pathadjacency effects are shown to influence the reflectance measurements. Low-altitude albedo histograms for heterogeneous scenes demonstrate higher contrast between sand and seagrass than is observed at higher altitudes, even after correction for path radiance and attenuation effects. For example, reflected light from bright sand scatters into the field of view of dark seagrass, while less light scatters out from the seagrass into the field of view of sand. This decreases the apparent sand albedo, and increases that for seagrass when viewed from higher altitudes, including aircraft. Evidence provided suggests that simple bottom classifications based upon expected albedo values for scene end members are in error unless the water depth is very shallow. ROV-collected reflectance data allows for analysis of individual end members and their collective influence on the total upwelling light signal at various altitudes, and suggests that remote-sensing retrievals of accurate bottom albedos for heterogeneous and high-contrast components of the bottom setting will not be possible without corrections for path-adjacency effects.
Scholar Commons Citation
Farmer, Andrew Scott, "Bottom Albedo Derivations Using Hyperspectral Spectrometry and Multispectral Video" (2005). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/2876
