Literature DB >> 29602501

Remote quantification of Cochlodinium polykrikoides blooms occurring in the East Sea using geostationary ocean color imager (GOCI).

Jae Hoon Noh1, Wonkook Kim2, Seung Hyun Son3, Jae-Hyun Ahn4, Young-Je Park5.   

Abstract

Accurate and timely quantification of widespread harmful algal bloom (HAB) distribution is crucial to respond to the natural disaster, minimize the damage, and assess the environmental impact of the event. Although various remote sensing-based quantification approaches have been proposed for HAB since the advent of the ocean color satellite sensor, there have been no algorithms that were validated with in-situ quantitative measurements for the red tide occurring in the Korean seas. Furthermore, since the geostationary ocean color imager (GOCI) became available in June 2010, an algorithm that exploits its unprecedented observation frequency (every hour during the daytime) has been highly demanded to better track the changes in spatial distribution of red tide. This study developed a novel red tide quantification algorithm for GOCI that can estimate hourly chlorophyll-a (Chl a) concentration of Cochlodinium (Margalefidinium) polykrikoides, one of the major red tide species around Korean seas. The developed algorithm has been validated using in-situ Chl a measurements collected from a cruise campaign conducted in August 2013, when a massive C. polykrikoides bloom devastated Korean coasts. The proposed algorithm produced a high correlation (R2=0.92) with in-situ Chl a measurements with robust performance also for high Chl a concentration (300mg/m3) in East Sea areas that typically have a relatively low total suspended particle concentration (<0.5mg/m3).
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cochlodinium polykrikoides; East Sea; GOCI; Ocean color; Quantification; Red tide; Remote sensing

Mesh:

Substances:

Year:  2018        PMID: 29602501     DOI: 10.1016/j.hal.2018.02.006

Source DB:  PubMed          Journal:  Harmful Algae        ISSN: 1568-9883            Impact factor:   4.273


  2 in total

1.  Evaluation of Chlorophyll-a Estimation Approaches Using Iterative Stepwise Elimination Partial Least Squares (ISE-PLS) Regression and Several Traditional Algorithms from Field Hyperspectral Measurements in the Seto Inland Sea, Japan.

Authors:  Zuomin Wang; Yuji Sakuno; Kazuhiko Koike; Shizuka Ohara
Journal:  Sensors (Basel)       Date:  2018-08-13       Impact factor: 3.576

2.  Phytoremediation of CYN, MC-LR and ANTX-a from Water by the Submerged Macrophyte Lemna trisulca.

Authors:  Małgorzata Kucała; Michał Saładyga; Ariel Kaminski
Journal:  Cells       Date:  2021-03-21       Impact factor: 6.600

  2 in total

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