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      Hyperspectral retrievals of phytoplankton absorption and chlorophyll-a in inland and nearshore coastal waters

      , , , , , ,
      Remote Sensing of Environment
      Elsevier BV

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          Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

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            Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters.

            For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.
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              Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: Analysis and parameterization

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                Author and article information

                Journal
                Remote Sensing of Environment
                Remote Sensing of Environment
                Elsevier BV
                00344257
                February 2021
                February 2021
                : 253
                : 112200
                Article
                10.1016/j.rse.2020.112200
                95ec15f7-8d26-4ca0-a227-6375d6c32c34
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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