황해에서의 부유물 분석 알고리즘 성능 검증 연구

Title
황해에서의 부유물 분석 알고리즘 성능 검증 연구
Alternative Title
Evaluation of the Suspended Particulate Matter (SPM) analysis algorithm in the Yellow Sea
Author(s)
민지은; 유주형; Xiong Wei
KIOST Author(s)
Ryu, Joo Hyung(유주형)
Publication Year
2015-10-07
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
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/25268
Bibliographic Citation
8th International Conference on Asian Marine Geology, pp.1, 2015
Publisher
KIGAM
Type
Conference
Language
English
Publisher
KIGAM
Related Researcher
Research Interests

Coastal Remote Sensing,RS based Marine Surveillance System,GOCI Series Operation,연안 원격탐사,원격탐사기반 해양감시,천리안해양관측위성 운영

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