탁한 연안 해역에서의 적조성 조류 증식에 대한 인공위성을 이용한 탐지

Abstract

Several planktonic dinoflagellates, including Cochlodinium polykrikoides (p), are known to produce red tides responsible for massive fish kills and serious economic loss in turbid Northwest Pacific (Korean and neighboring) coastal waters during summer and fall seasons. In order to mitigate the impacts of these red tides, it is therefore very essential to detect, monitor and forecast their development and movement using currently available remote sensing technology because traditional ship-based field sampling and analysis are very limited in both space and temporal frequency. Satellite ocean color sensors, such as Sea-viewing Wide Field-of-view Sensor (SeaWiFS), are ideal instruments for detecting and monitoring these blooms because they provide relatively high frequency synoptic information over large areas. Thus, the present study attempts to evaluate the red tide index methods (previously developed by Ahn and Shanmugam et al., 2006) to identify potential areas of red tides from SeaWiFS imagery in Korean and neighboring waters. Findings revealed that the standard spectral ratio algorithms (OC4 and LCA) applied to SeaWiFS imagery yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered red tides in the focused waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent red tide occurrences in high scattering and absorbing waters off the Korean and Chinese coasts. The results suggest that the red tide index methods for the early detection of red tides blooms can provide state managers with accurate identification of the extent and location of blooms as a management tool.