황해에서의 부유물 분석 알고리즘 성능 검증 연구

Abstract

The Yellow Sea is an optically complex water with the features of regional sea such as river discharge, bottom topography and sedimentary facies, etc. Furthermore, the monsoon from northwest in winter season enhance its complexity. In this area, the ocean color is influenced by lots of water constituents such as chlorophyll, suspended particulate matter (SPM), dissoved organic matter (DOM), bacteria, bubbles, and so on. Among them, SPM is the most important factor for the environmental monitoring of the Yellow Sea. One of the effective technique of SPM analysis for the large area is an ocean color remote sensing. But it is difficult to estimate the pricise values for the wide range of the SPM concentration, especially, extremely turbid values from the estuarine area of the Yangtze River (>1000 g/m3). In this study we would like to evaluate the existing SPM algorithm using in situ. dataset obtained from the extremely turbid waters of Korea (Gyeonggi Bay and coastal area of Mokpo) and China (Yangtze Estuary and coastal waters of Jiangsu). The Geostationary Ocean Color Imager (GOCI), world’s first geostationary satellite for ocean color, has been operational since July 2010. Using a large number of image data accumulated since the launch of the satellite we used the GOCI match-up dataset for SPM algorithm evaluation. In situ. bio-optical and marine environmental data obtained from 2009 to 2014 in the Yellow Sea were anarea, the ocean color is influenced by lots of water constituents such as chlorophyll, suspended particulate matter (SPM), dissoved organic matter (DOM), bacteria, bubbles, and so on. Among them, SPM is the most important factor for the environmental monitoring of the Yellow Sea. One of the effective technique of SPM analysis for the large area is an ocean color remote sensing. But it is difficult to estimate the pricise values for the wide range of the SPM concentration, especially, extremely turbid values from the estuarine area of the Yangtze River (>1000 g/m3). In this study we would like to evaluate the existing SPM algorithm using in situ. dataset obtained from the extremely turbid waters of Korea (Gyeonggi Bay and coastal area of Mokpo) and China (Yangtze Estuary and coastal waters of Jiangsu). The Geostationary Ocean Color Imager (GOCI), world’s first geostationary satellite for ocean color, has been operational since July 2010. Using a large number of image data accumulated since the launch of the satellite we used the GOCI match-up dataset for SPM algorithm evaluation. In situ. bio-optical and marine environmental data obtained from 2009 to 2014 in the Yellow Sea were an