Application of optical remote sensing imagery for detection of red tide algal blooms in Korean waters

Abstract

The present study involves analyzing chlorophyll-a (Chl-a) from SeaWiFS data collected over the period 1998-2002 to better understand the spatial and temporal aspects of red tide algal blooms created by Cochlodinium polykrikoides species in the enclosed and semi-enclosed bays of the South Sea of Korea. NOAA-AVHRR data is analyzed for sea surface temperature (SST) to elucidate physical factors affecting these aspects and abundance of Cochlodinium.p blooms. The time series Chl-a give an impression that recent red tide events with higher concentrations appear to have spanned more than 8 weeks in summer and fall seasons and were widespread in most of the South Sea coastal bays and neighboring ocean waters. The Chl-a estimates from SeaWiFS data appeared to be useful in demonstrating spatial and temporal aspects of these blooms, but uniquely identification of Cochlodinium.p from non-bloom and sediment dominated waters remains ineffective with these data. Thus the classical techniques such as Forward Principal Component Analysis (FPCA) and Minimum Spectral Distance (MSD) are attempted on both low spatial resolution SeaWiFS ocean color image data and high spatial resolution Landsat-7 ETM+ data. In September 2000, when an exchange of water masses took place off the southeastern coast, dense and mixed phases of the Cochlodinium.p blooms were conspicuous in the spectrally transformed SeaWiFS image. The existence of these phases inferred from SeaWiFS imagery was verified with both the atmospherically corrected and in-situ radiance spectra collected from these regions. Findings show that the application of SeaWiFS to uniquely identify Cochlodinium.p bloom from mixed and turbid plume was not feasible, but it was very effective with Landsat-7 ETM+ imagery detecting intricate and filament-like patterns of the Cochlodinium.p blooms and its dynamics owing to numerous physical mechanisms as determined by sea surface temperature from AVHRR infrared data.