한국 연안에서 발생하는 Cochlodinium polykrikoides 유해 적조의 광학적 구별

Abstract

Over the past decades, harmful algal blooms (HABs) have been a significant threat to fishery industries, human, and economies throughout the world. In Korea, large- and small-scale harmful bloom events of the dinoflagellate Cochlodinium polykrikoides have continuously occurred in the southern coastal region as optically complex waters during summer and autumn season since 1985. These blooms have caused great damages to the aquaculture industry since 1995 (e.g. economic loss of 65 million dollars in 1995). Developing feasible approaches for synoptic and subsequent monitoring and the early detection of C. polykrikoides blooms is highly required to mitigate the losses of fishery industry and assist in fisheries management and enhancement of tourism industries. In order to effectively detect and monitor the spatial and temporal distributions of widespread C. polykrikoides blooms, in-situ radiometric measurements and/or satellite remote sensing has been employed. In this study, we tried to discriminate C. polykrikoides blooms based on remote sensing reflectance (Rrs). The large data set (n=910) of Rrs(λ) for C. polykrikoides blooms and non-harmful blooms in various water types were simulated using Hydrolight software (radiative transfer model) to overcome the lack of in-situ Rrs(λ) data. We analyzed Rrs(λ) using the second derivative analysis and similarity index to find out the differences between two kinds of Rrs(λ)ykrikoides have continuously occurred in the southern coastal region as optically complex waters during summer and autumn season since 1985. These blooms have caused great damages to the aquaculture industry since 1995 (e.g. economic loss of 65 million dollars in 1995). Developing feasible approaches for synoptic and subsequent monitoring and the early detection of C. polykrikoides blooms is highly required to mitigate the losses of fishery industry and assist in fisheries management and enhancement of tourism industries. In order to effectively detect and monitor the spatial and temporal distributions of widespread C. polykrikoides blooms, in-situ radiometric measurements and/or satellite remote sensing has been employed. In this study, we tried to discriminate C. polykrikoides blooms based on remote sensing reflectance (Rrs). The large data set (n=910) of Rrs(λ) for C. polykrikoides blooms and non-harmful blooms in various water types were simulated using Hydrolight software (radiative transfer model) to overcome the lack of in-situ Rrs(λ) data. We analyzed Rrs(λ) using the second derivative analysis and similarity index to find out the differences between two kinds of Rrs(λ)