Modeling spectral reflectance of optically complex waters using bio-optical measurements from Tokyo Bay

In this parameterization scheme, an unsupervised classification was applied in the hyper-spectral space of reflectance, leading to three spectrally distinct optical water types. The reflectance model was parameterized for the entire data set, and then parameterized for each of the water types. The three sets of type-specific model parameters, which define corresponding IOP submodels, are believed to accommodate differences in the optical properties of the in-water constituents. The parameterized reflectance model was evaluated by both reconstructing measured reflectance spectra and solving for the nonlinear inverse problem to retrieve in-water constituent concentrations. The model accuracy was significantly improved in the forward direction for classified waters over that of non-classified waters, but no significant improvement was achieved in the retrieval accuracy (inverse direction). A larger data set with greater resolution of constituent inherent optical properties would likely improve the modeling results.