1998
DOI: 10.1364/ao.37.006329
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Hyperspectral remote sensing for shallow waters I A semianalytical model

Abstract: For analytical or semianalytical retrieval of shallow-water bathymetry and/or optical properties of the water column from remote sensing, the contribution to the remotely sensed signal from the water column has to be separated from that of the bottom. The mathematical separation involves three diffuse attenuation coefficients: one for the downwelling irradiance (K(d)), one for the upwelling radiance of the water column (K(u)(C)), and one for the upwelling radiance from bottom reflection (K(u)(B)). Because of t… Show more

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Cited by 520 publications
(396 citation statements)
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“…In optically complex waters, the optical properties of the water column are typically influenced by nonalgal particulate matter, colored dissolved organic matter, and phytoplankton [IOCCG, 2000], and unlike oceanic waters, the nonalgal constituents do not necessarily covary with respect to phytoplankton abundance. Regarding optically shallow waters, these can be characterized as zones in which light reflected from the seafloor influences the waterleaving radiance signal [Lee et al, 1998] thereby confounding contemporary ocean color algorithms developed for optically deep waters [Cannizzaro and Carder, 2006;Qin et al, 2007;Zhao et al, 2013] (see Appendix A for further discussion). Whilst a range of ocean color algorithms have been developed and proven effective within optically complex waters [Doerffer and Schiller, 2007;Smyth et al, 2006;Werdell et al, 2013a], only a few approaches for optically shallow waters have been published [Barnes et al, 2014Brando et al, 2012] with none in operation that explicitly use pre-existing water column depth and benthic albedo data sets to improve IOP retrievals.…”
Section: Key Pointsmentioning
confidence: 99%
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“…In optically complex waters, the optical properties of the water column are typically influenced by nonalgal particulate matter, colored dissolved organic matter, and phytoplankton [IOCCG, 2000], and unlike oceanic waters, the nonalgal constituents do not necessarily covary with respect to phytoplankton abundance. Regarding optically shallow waters, these can be characterized as zones in which light reflected from the seafloor influences the waterleaving radiance signal [Lee et al, 1998] thereby confounding contemporary ocean color algorithms developed for optically deep waters [Cannizzaro and Carder, 2006;Qin et al, 2007;Zhao et al, 2013] (see Appendix A for further discussion). Whilst a range of ocean color algorithms have been developed and proven effective within optically complex waters [Doerffer and Schiller, 2007;Smyth et al, 2006;Werdell et al, 2013a], only a few approaches for optically shallow waters have been published [Barnes et al, 2014Brando et al, 2012] with none in operation that explicitly use pre-existing water column depth and benthic albedo data sets to improve IOP retrievals.…”
Section: Key Pointsmentioning
confidence: 99%
“…Many recent approaches such as the Hyperspectral Optimization Process Exemplar (HOPE), a semianalytical inversion algorithm developed by Lee et al [1998], and the Comprehensive Reflectance Inversion based on Spectrum matching and Table Look up (CRISTAL), a spectral matching look-up-table algorithm developed by Mobley et al [2005], have been developed for simultaneous retrieval of bathymetry, benthic types, and IOPs. The HOPE algorithm and its variants (e.g., Goodman and Ustin, [2007]; ALUT-Hedley et al…”
Section: Key Pointsmentioning
confidence: 99%
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