Derivation and discrimination of Case-II water constitutents in a multicomponent bloom using MOS remote sensing data

Abstract

DLR s imaging spectrometer MOS on the Indian satellite IRS-P3 detected in May 1998 a water discoloration near the coast of Cornwall (UK) at the English Channel indicating a bloom of Coccolithophores in combination with other types of algae. The same event was parallel found by SeaWifs. The water leaving radiance is strongly influenced by the backscattering of the coccolithophores that exceeds the contri-bution of the other water constituents. This leds to a masking effect for the determination of the water constituent quantities and increases the part of the water body to the total signal that reaches the sensor at all wavelengths in the vis/nir spectral region. Atmospheric correction procedures are also affected. Simple Color ratio algorithms for chlorophyll concentrations normally fail or result in huge deviations. Therefore algorithms for the retrieval of water constituents and the distinction between different types have to use the differences in spectral signatures of these geophysical parameters. We developed a linear estimation algorithm to derive water constituents and atmospheric turbidity, exploiting Principal Component Analysis of modeled top-of-atmosphere and experimental radiance data sets. The inherent atmospheric correction of the algorithm helps to minimize the deviation of the increased radiance due to the coccolithophores. The presented paper will show derived maps of chlorophyll like pigments, sediments and aerosol optical thickness of the bloom near the British coast. It will demonstrate promising the potential of the new MOS-algorithm for qualitative retrieval and the distinction of different water constituents in coastal waters. The retrieved geophysical parameters will be compared and discussed to the results of other algorithms applied to the MOS and SeaWifs data.