Evaluation of ocean color products from Korean Geostationary Ocean Color Imager (GOCI) in Jiaozhou Bay and Qingdao coastal area

被引:3
|
作者
Yang, Qian [1 ]
Du, Libin [1 ]
Liu, Xiaoyan [1 ]
Hu, lianbo [1 ]
Chen, Shuguo [1 ]
Liu, Yan [1 ]
Wang, Zhaoyu [1 ]
Wang, Zhangjun [1 ]
Zhou, Yan [1 ]
机构
[1] Shandong Acad Sci, Inst Oceanog Instrumentat, Qingdao 266001, Peoples R China
关键词
remote sensing reflectance; chlorophyll-a concentration; GOCI; MODIS; Jiaozhou Bay; Qingdao coast; RADIANCE;
D O I
10.1117/12.2069114
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The Geostationary Ocean Color Imager (GOCI) is the first geostationary ocean color satellite sensor launched in June 2010 on board the South Korean Communication, Ocean and Meteorological Satellite (COMS). The GOCI has a local coverage area of the western Pacific Ocean including Bohai, Yellow Sea and East Sea of China. Jiaozhou Bay is a semienclosed basin in the western part of the Yellow Sea, which is an important representative of gulf ecosystem in the North Temperate Zone. The GOCI data can provide useful information with an-hour temporal and 500-m spatial resolutions for monitoring oceanic and atmospheric process in Jiaozhou Bay. The performance of the atmospheric and optical algorithms of GOCI was evaluated by comparing with the simultaneous data from MODIS/Aqua. The match-up products include remote sensing reflectance (R-rs) and chlorophyll-a concentration ([chl-a]) and they were derived by GDPS software for GOCI data and SeaDAS software for MODIS and GOCI data, respectively, using default atmospheric correction and bio-optical algorithms. Our analyses show that GOCI products (i.e., R-rs(490), R-rs(555) and [chl-a]) are compared well with MODIS products. GOCI shows a potential capability of oceanography investigations in Jiaozhou Bay and Qingdao coastal area. The consistency of Rrs between GOCI and MODIS is relatively good but significant difference was observed in [chl-a] especially in Jiaozhou Bay. Moreover, it is suggested to improve GOCI standard atmospheric correction algorithm for high turbid water and cloud detection to increase data utilization.
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页数:10
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