A STUDY ON DISCRIMINATION BETWEEN RED TIDE SPECIES USING GOCI

Title
A STUDY ON DISCRIMINATION BETWEEN RED TIDE SPECIES USING GOCI
Author(s)
신지선; 김근용; 민승환; 유주형
KIOST Author(s)
Kim, Keunyong(김근용)Ryu, Joo Hyung(유주형)
Alternative Author(s)
신지선; 김근용; 유주형
Publication Year
2018-05-11
Abstract
Cochlodinium polykrikoides and Prorocentrum donghaiense are harmful red tide species that are the most damaging in the Korean coastal waters and the East China Sea. In addition, harmless red tide species such Noctiluca scintillans, Prorocentrum dentatum frequently represented in the Korean coastal waters. However, Harmless red tide species as well as harmful red tide species in coastal regions can kill organisms in aquaculture farms and be detrimental to marine ecosystem health. To minimize its negative impacts and construct red tide surveillance system, an accurate and near-real time technique is needed for detecting and discriminating the red tide species, which can rely on satellite-based ocean colour sensors, such as Geo-stationary Ocean Color Imager(GOCI). Here, the schematic procedure for discriminating various red tide species was developed based on the differences of GOCI nLw spectral shape. For this purpose, the spectral characteristics of various red tide species were analyzed by referring to previous studies and red tide report from National Institute of Fisheries Science(NIFS). The slope of various red tide species occurred in the spectral range from 490 to 555 nm can be an indicator to distinguish each red tide species. Also, the groups are divided through absolute value of nLw slope(490, 555)/nLw slope(443,490). The schematic procedure were developed for discrimination of various red tide specie blooms, based on the distinct spectral differences. As a result of applying the schematic procedure for red tide surveillance to GOCI, comparison with reference data showed that our schematic procedure provides reliable information on red tide detection and species classification. It may allow red tide surveillance system to be carried out more efficiently.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23374
Bibliographic Citation
International Symposium on Remote Sensing 2018, pp.358 - 361, 2018
Publisher
KSRS/CSPRS/RSSJ/EMSEA
Type
Conference
Language
English
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