This paper presents an analysis of several in-water algorithms developed using a large number of
bio-optical data collected in Korean and neighbouring ocean waters. The upward and downward
light fields measured in these waters were normalized to provide remote sensing reflectance
(Rrs)
from which the variations in sun-induced chlorophyll-a (Chl-a) fluorescence
from phytoplankton biomass were analysed and the fluorescence line height
(ΔFlu) was measured using
a baseline method. ΔFlu
measurements were related to in situ Chl-a concentrations (used
as an index for quantifying the algal material) to obtain the
ΔFlu(681),
ΔFlu(688)
and ΔFlu(area)
algorithms, which were compared with those from standard spectral ratios of the remote sensing reflectance,
Rrs(444)/Rrs(554)
and Rrs(490)/Rrs(554). Comparison revealed the correlation coefficients
(r2)
0.88–0.90 for the fluorescence algorithms and 0.79–0.85 for the spectral ratios algorithms. A
validation analysis using a new data set illustrated the merits of these algorithms in Case II
waters. Fluorescence-based algorithms tended to reproduce in situ Chl-a concentrations (from 0.1 to
82 mg m−3), whereas standard spectral ratios algorithms gave inconsistent estimates, probably caused
by the interference of inorganic sediment and dissolved organic matter in these waters. For
measurements of the sun-induced Chl-a fluorescence signal in coastal waters, this study
discusses the requirements and provides the optimal channels to be adopted in the
design of the new generation ocean colour sensors planned in the near future.