Paper
8 July 1994 Analysis of high spectral resolution coastal ocean imagery: statistical, empirical, and analytical investigations
Michael K. Hamilton, Stuart H. Pilorz, Curtiss O. Davis, Jeannette M. van den Bosch, W. Joseph Rhea
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Abstract
A combination of towed and stationary shipboard measurements, bio-optical mooring data, and a series of AVIRIS images were acquired near an offshore sewage outfall which services the Los Angeles metropolitan area. The image containing the outfalls and in-situ measurements was examined using statistical techniques to derive the spectral components responsible for salient variations. These computed components agree quite well with spectra which were hand selected to qualitatively represent the scene. Suspended sediment and aquatic vegetation detection were investigated using spectral derivative techniques, which were quite successful in showing the extent of offshore kelp forests and storm-induced resuspension of previously deposited outfall effluent, or the effluent itself. The in-situ and remote sensing measurements were used to constrain a numerical model of the underwater light field, and the scattering properties along a surface transect were investigated using two phase functions. Using a one-term Henyey-Greenstein function with a backscattering ratio of nearly 30%, we were able to reproduce the remotely- sensed radiance, suggesting that the particulates had a size distribution skewed toward small. These investigations show the utility of high spectral resolution in determining the extent and character of several important natural and anthropogenic components of coastal areas, as well as parameterizing models of the inherent optical properties of the underwater light field.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael K. Hamilton, Stuart H. Pilorz, Curtiss O. Davis, Jeannette M. van den Bosch, and W. Joseph Rhea "Analysis of high spectral resolution coastal ocean imagery: statistical, empirical, and analytical investigations", Proc. SPIE 2231, Algorithms for Multispectral and Hyperspectral Imagery, (8 July 1994); https://doi.org/10.1117/12.179772
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KEYWORDS
Silicon

Statistical analysis

Data modeling

Spectral resolution

Vegetation

Information operations

Molybdenum

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