Deriving optical metrics of coastal phytoplankton biomass from ocean colour

An approach to develop accurate local models for the estimation of chlorophyll a concentration (Chl a) and spectral phytoplankton absorption (aph(λ)) from hyperspectral in situ measurements of remote sensing reflectance (Rrs(λ)) in an optically complex water body is presented. The models are based on empirical orthogonal function (EOF) analysis of integral-normalised Rrs(λ) spectra, and spectral normalisation was found to be key to the models’ success. Accurate model estimates of both Chl a and aph(λ) were obtained, with R2 values in log10 space (N = 42) of 0.839 found for Chl a, and for aph(λ), R2 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 aph(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 R2 values obtained within ~ 1% of the hyperspectral (101 wavelengths) R2 values for both Chl a and aph(λ). That the reduced-wavelength resolution models performed as well as the hyperspectral models points to their potential utility for satellite sensors.

► In situ reflectance spectra of coastal waters are characterised using EOF analysis.
► EOF scores are variables in models of chlorophyll a and phytoplankton absorption.
► The models perform very well in an optically complex coastal water body.
► The approach shows promise for application to satellite reflectance.