Hyperspectral and multispectral ocean color inversions to detectPhaeocystis globosablooms in coastal waters

Abstract

Identification of phytoplankton groups from space is essential to map and monitor algal blooms in coastal waters, but remains a challenge due to the presence of suspended sediments and dissolved organic matter which interfere with phytoplankton signal. On the basis of field measurements of remote sensing reflectance (Rrs(λ)), bio‐optical parameters, and phytoplankton cells enumerations, we assess the feasibility of using multispectral and hyperspectral approaches for detecting spring blooms ofPhaeocystis globosa(P. globosa). The two reflectance ratios (Rrs(490)/Rrs(510) andRrs(442.5)/Rrs(490)), used in the multispectral inversion, suggest that detection ofP. globosablooms are possible from current ocean color sensors. The effects of chlorophyll concentration, colored dissolved organic matter (CDOM), and particulate matter composition on the performance of this multispectral approach are investigated via sensitivity analysis. This analysis indicates that the development of a remote sensing algorithm, based on the values of these two ratios, should include information aboutCDOMconcentration. The hyperspectral inversion is based on the analysis of the second derivative ofRrs(λ) (dλ2Rrs). Two criteria, based on the position of the maxima and minima ofdλ2Rrs, are established to discriminate theP. globosablooms from diatoms blooms. We show that the position of these extremes is related to the specific absorption spectrum ofP. globosaand is significantly correlated with the relative biomass ofP. globosa. This result confirms the advantage of a hyperspectral over multispectral inversion for species identification and enumeration from satellite observations of ocean color.