Artigas, Luis Felipe

Astoreca, R.

Guiselin, N.

Loisel, Hubert

Lubac, B.

Mériaux., X.

International audienceIdentification of phytoplankton groups from space is essential to map and monitoralgal blooms in coastal waters, but remains a challenge due to the presence of suspendedsediments and dissolved organic matter which interfere with phytoplankton signal. Onthe basis of field measurements of remote sensing reflectance (Rrs (l)), bio-opticalparameters, and phytoplankton cells enumerations, we assess the feasibility of usingmultispectral and hyperspectral approaches for detecting spring blooms of Phaeocystisglobosa (P. globosa). The two reflectance ratios (Rrs (490)/Rrs (510) and Rrs (442.5)/Rrs (490)), used in the multispectral inversion, suggest that detection of P. globosa bloomsare possible from current ocean color sensors. The effects of chlorophyll concentration,colored dissolved organic matter (CDOM), and particulate matter composition on theperformance of this multispectral approach are investigated via sensitivity analysis. Thisanalysis indicates that the development of a remote sensing algorithm, based on the valuesof these two ratios, should include information about CDOM concentration. Thehyperspectral inversion is based on the analysis of the second derivative of Rrs (l) (dl2Rrs ).Two criteria, based on the position of the maxima and minima of dl2Rrs , are establishedto discriminate the P. globosa blooms from diatoms blooms. We show that the position ofthese extremes is related to the specific absorption spectrum of P. globosa and issignificantly correlated with the relative biomass of P. globosa. This result confirms theadvantage of a hyperspectral over multispectral inversion for species identification andenumeration from satellite observations of ocean colo

Lubac, Bertrand

Guiselin, Natacha

Mériaux, Xavier

HAL-IRD

Hyperspectral versus multispectral remote sensing approach to detect phytoplankton blooms in coastal waters : application to a Phaeocystis bloom.

Hyperspectral versus multispectral remote sensing approach to detect phytoplankton blooms in coastal waters : application to a Phaeocystis bloom.

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