GOCI 자료를 이용한 서해안 갈조 탐지 연구

Title
GOCI 자료를 이용한 서해안 갈조 탐지 연구
Alternative Title
Remote sensing of Sargassum using an anomaly detection technique in the Yellow Sea with GOCI data
Author(s)
김나은; 김원국; 이보람; 안재현; 박영제
KIOST Author(s)
Ahn, Jae Hyun(안재현)Park, Young Je(박영제)
Publication Year
2016-12-14
Abstract
A large amount of the Sargassum horneri (S.horneri) came to the Yellow Sea in 2015. This resulted in a scarcity of oxygen in the ocean, which in turn caused the deaths of many fish and other marine organisms. Not only did the arrival of the S.horneri caused harm to the inhabitants but it was also responsible for the insufferable stench. Since the S.horneri is a nuisance to deal with, it is crucial to detect it before it inflicts more damage. This study presents the results of S.horneri detection using Geostationary Ocean Color Imager (GOCI) data during the period between January and June in 2015. GOCI data are one of the best tools for detecting the S.horneri because it collects data 8 times per day. The data can also be used to observe the temporal variations of the S.horneri distribution in the ocean frequently. We first used normalized difference vegetation index (NDVI) using 660nm and 745nm of GOCI to detect all floating vegetation algae. With NDVI only, however, S.horneri detection is challenging in turbid waters because NDVI is elevated by the high NIR signals due to mineral particles in turbid waters. So, in the next step, we employed an anomaly detection technique to increase the detection rate of S.horneri both in clear and turbid waters. Finally, we tried to differentiate between S.horneri and other floating algae and estimated its coverage within a pixel.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/24247
Bibliographic Citation
The 4th Asian/13th Korea-Japan Workshop on Ocean Color, pp.37, 2016
Publisher
Burapha
Type
Conference
Language
English
Publisher
Burapha
Related Researcher
Research Interests

Ocean Color Remote Sensing,Satellite Applications,Ocean color Algorithm,해양원격탐사,위성활용,해색 알고리즘

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