Estimation of Phytoplankton Accessory Pigments From Hyperspectral Reflectance Spectra: Toward a Global Algorithm

Abstract

Phytoplankton community composition in the ocean is complex and highly variable over a wide range of space and time scales. Able to cover these scales, remote‐sensing reflectance spectra can be measured both by satellite and by in situ radiometers. The spectral shape of reflectance in the open ocean is influenced by the particles in the water, mainly phytoplankton and covarying nonalgal particles. We investigate the utility of in situ hyperspectral remote‐sensing reflectance measurements to detect phytoplankton pigments by using an inversion algorithm that defines phytoplankton pigment absorption as a sum of Gaussian functions. The inverted amplitudes of the Gaussian functions representing pigment absorption are compared to coincident High Performance Liquid Chromatography measurements of pigment concentration. We determined strong predictive capability for chlorophylls a, b, c1+c2, and the photoprotective carotenoids. We also tested the estimation of pigment concentrations from reflectance‐derived chlorophyll a using global relationships of covariation between chlorophyll a and the accessory pigments. We found similar errors in pigment estimation based on the relationships of covariation versus the inversion algorithm. An investigation of spectral residuals in reflectance data after removal of chlorophyll‐based average absorption spectra showed no strong relationship between spectral residuals and pigments. Ultimately, we are able to estimate concentrations of three chlorophylls and the photoprotective carotenoid pigments, noting that further work is necessary to address the challenge of extracting information from hyperspectral reflectance beyond the information that can be determined from chlorophyll a and its covariation with other pigments.

Inversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance properties

“…1. The in situ measurements of water-leaving signals were collected using a Satlantic HyperPro tethered in buoy mode (Chase et al, 2017). In this study we compared our retrieval results with these HyperPro measurements, all of which are available from NASA's SeaBASS (NASA SeaBASS webpage, 2019).…”

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

“…, Chase et al. ). A minimum spectral resolution of 6–8 nm is required in the visible wavelengths to separate diagnostic accessory pigments of phytoplankton as well as fluorescence signals in the reflectance spectrum (Dekker and Pinnel ).…”

“…High spectral resolution is also required to separate aquatic constituents by their light absorption, scattering, and fluorescence characteristics (PACE SDT 2012). These include chlorophyll a absorption at 435-438 nm, other accessory pigment absorption features between 550 and 900 nm, and fluorescence by chlorophyll a and other pigments (Dierssen et al 2015b, Hu et al 2005, Chase et al 2017. A minimum spectral resolution of 6-8 nm is required in the visible wavelengths to separate diagnostic accessory pigments of phytoplankton as well as fluorescence signals in the reflectance spectrum (Dekker and Pinnel 2017).…”

Retrieval of Phytoplankton Pigments from Underway Spectrophotometry in the Fram Strait

“…The amplitude of each Gaussian function is assumed to represent the magnitude of the absorption coefficient of a specific pigment or pigment group at the Gaussian peak wavelength, based on known pigment absorption properties determined in laboratory analyses. This method simultaneously retrieves the concentrations of chlorophyll-a, chlorophyll-b, chlorophyll-c and carotenoids [11,[21][22][23] or of chlorophyll-a and phycocyanin [24,25]. However, the retrieval accuracy is generally limited by the variations in pigment package effect of field samples.…”