Deriving optical metrics of coastal phytoplankton biomass from ocean colour

Abstract An approach to develop accurate local models for the estimation of chlorophyll a concentration ( Chl a ) and spectral phytoplankton absorption ( a ph ( λ )) from hyperspectral in situ measurements of remote sensing reflectance ( R rs ( λ )) in an optically complex water body is presented. The models are based on empirical orthogonal function (EOF) analysis of integral-normalised R rs ( λ ) spectra, and spectral normalisation was found to be key to the models’ success. Accurate model estimates of both Chl a and a ph ( λ ) were obtained, with R 2 values in log 10 space ( N  = 42) of 0.839 found for Chl a , and for a ph ( λ ), R 2 values ranging from 0.771 (547 nm) to 0.910 (655 nm). A statistical resampling exercise to create training and test data sets showed that stable models could be built with ~ 15 training spectra and corresponding measurements of Chl a and a ph ( λ ), providing important guidance for the implementation of this approach at other locations. The applicability of the models to a reduced-wavelength resolution (8 wavebands) dataset was tested, and showed that reduction in wavelength resolution had little impact on the models’ skill, with R 2 values obtained within ~ 1% of the hyperspectral (101 wavelengths) R 2 values for both Chl a and a ph ( λ ). That the reduced-wavelength resolution models performed as well as the hyperspectral models points to their potential utility for satellite sensors.