Spectral characterization of ocean color images during fitoplâcton blooms in Patos Lagoon

Abstract

Coastal lagoon are extremely dynamic environments, with primary production rates varing with physical factors such us rainfall, salinity tides and wind system. There are strong longitudinal gradients, and they determine the spatial distribution of the primary producers. In Brazil, we can find one of the largest coastal lagoon in the world, the Patos Lagoon, which presents records of chlorophyll-a concentration, estimated from biomass, changing between 0.4 and 41.5 mg m-3. Phytoplankton blooms are characterized with a accentuated development in determined phytoplankton groups number, reaching higher values of biomass and producing changes in the color of the water superficial layer. Based on the fact that the color is associated with the taxonomic group, it is possible to observe changes in the color of the water with the dominant species, being able to generate different specters for each bloom. In a remote way, it is possible to observe changes in water color by using sensors aboard satellites, as MODIS/Aqua and SeaWiFS, that have the capacity to collect the light reflected by water bodies in many wave lengths and, by using algorithms, change the values observed into products, as chlorophyll-a and reflectance values. Taking into account those factors, the present work has as objective to use the orbital images to characterize in a spectral way the blooms observed in the Patos Lagoon during the years between 2002 and 2005, observing if there is a seasonal and spacial pattern in the specter and if it can be associated with dominant taxonomic groups. For that, the empirical orthogonal function and principal component analysis will be done, being possible to correlate a unique spectral behavior with a taxonomic group. As a final product, we plan to correlate taxonomic groups for each bloom in function with the specter, observing if there is a fluctuation in the different Patos Lagoon areas in the same image, and how this change during years.