Cochlodinium polykrikoides red tide detection in the South Sea of Korea using spectral classification of MODIS data

Abstract

To distinguish true red tide water (particularly Cochlodinium polykrikoides blooms) from non-red tide water (false satellite high chlorophyll water) in the South Sea of Korea, we developed a systematic classification method using spectral information from MODIS level products and applied it to five different harmful algal bloom events. Red tide and nonred tide waters were classified based on four different criteria. The first step revealed that the radiance peaks of potential red tide water occurred at 555 and 678 nm. The second step separated optically different waters that were influenced by relatively low and high contributions of colored dissolved organic matter (CDOM) (including detritus) to chlorophyll. The third and fourth steps discriminated red tide water from non-red tide water based on the blue-to-green ratio in areas with lower and higher contributions of CDOM to chlorophyll, respectively. After applying the red tide classification (using the four criteria), the spectral response of the red tide water, which is influenced by pigment concentration, showed different slopes for the blue and green bands (lower slope at blue bands and higher slope at green bands). The opposite result was found for non-red tide water, due to decreasing phytoplankton absorption and increasing detritus/CDOM absorption at blue bands. The results were well matched with the discoloration of water (blue to dark red/brown) and delineated the areal coverage of C. polykrikoides blooms, revealing the nature of spatial and temporal variations in red tides. This simple spectral classification method led to increase user accuracy for C. polykrikoides and non-red tide blooms (>46% and >97%) and provided a more reliable and robust identification of red tides over a wide range of oceanic environments than was possible using chlorophyll a concentration, chlorophyll anomaly, fluorescence analysis, or proposed red tide detection algorithms. © 2011 Korea Ocean Research & Development Institute (KORDI) and the Korean Society of Oceanography (KSO) and Springer Netherlands.