Recent and future imaging spectrometers in air and orbit portend a revolution in capability for coastal and inland water studies. Bayesian model inversion methods are a powerful tool for analyzing these data. Their flexible prior distributions provide distinct advantages for the water optics environment, including numerical stability of the inversion, the ability to incorporate ancillary data, and rigorous propagation of uncertainties in the parameter estimates. This talk highlights an Optimal Estimation (OE) methodology from recent work which demonstrates closed uncertainty accounting for coastal and inland waters.
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