Monitoring blooms and surface accumulation of cyanobacteria in the Curonian Lagoon by combining MERIS and ASAR data

Abstract

This study shows how different remote sensing techniques can be used to distinguish between surface accumulations (scum) and dense blooms of cyanobacteria in the Curonian Lagoon, the largest lagoon in Europe. Cyanobacteria blooms are a major concern in this region due to water quality issues interfering with the conservation of the whole ecosystem. Chlorophyll-a (Chl-a) concentrations can be extremely high (up to about 500mg/m3 in some cases) during cyanobacteria blooms, which are often associated with a surface accumulation of algae. The Medium Resolution Imaging Spectrometer (MERIS) was used to acquire 52 images covering the summers of 2004 to 2011. These images were analyzed to map Chl-a concentrations and the presence of scum using two different band ratio algorithms applied to atmospherically-corrected data. The results identify wind speed as the main driving factor in the surface accumulation of algae, as well as in the spatial distribution of Chl-a. The utility of microwave images was also assessed, as since any cloud cover obviously hampers the use of optical data. Advanced Synthetic Aperture Radar (ASAR) images were collected synchronously with the MERIS data and the normalized radar cross-section (NRCS) signal was corrected for the contribution of wind for the purposes of correlating the results with the MERIS-derived Chl-a concentrations. In general, there was a stepwise decrease in the NRCS for high values of Chl-a (>50mg/m3) with wind speeds in the range of 2 to 6m/s. Under these conditions, our results demonstrate that optical and microwave signals can be used in combination to improve our understanding of cyanobacteria blooming.