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

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 (R=0.92) with in-situ Chl a measurements with robust performance also for high Chl a concentration (300mg/m) in East Sea areas that typically have a relatively low total suspended particle concentration (<0.5mg/m).

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

“…. , 16:00 hours and in this case, the reference is the value at 13:00 hours, that is, x reference = X 13:00 . The R∆ t [%] is an indicator of uncertainties that are expected depending on the time of the day, assuming no changes in the in-water properties due to biological or biogeochemical processes.…”

“…A variety of algorithms have been developed that utilize GOCI spectral observations to retrieve water-column constituents, including concentrations of the phytoplankton pigment chlorophyll-a (Chl-a) and total suspended material (TSM) [11][12][13]. GOCI data have also been used to determine the diurnal submesoscale variability of turbidity fronts [14], internal waves [15], red tides and green algae [16,17]. The success of GOCI has prompted the development of future GEO missions such as GOCI-II, scheduled to be launched in 2019, and formulation studies on a European geostationary satellite Ocean Color Advanced Permanent Imager (GEO-OCAPI).…”

Using Copernicus Sentinel-2 and Sentinel-3 data to monitor harmful algal blooms in Southern Chile during the COVID-19 lockdown

“…Intensive efforts have been made in some countries to detect with satellites specific blooms of the two species evaluated in this research: Cochlodinium sp. (Noh et al, 2018) and Lepidodinium chlorophorum (Jegou, 2013;Morozov et al, 2013;Sourisseau et al, 2016).…”

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

“…Having a high degree of spatial and temporal coverage over a large scale is convenient for monitoring HABs. Several studies have shown distributions of HABs using satellite imagery and chlorophyll a (Chl- a ) concentration measurements [ 7 , 8 ]. Chl- a concentration in water is a major indicator of a trophic state and oceanic Chl- a concentration is the most common property characterizing first trophic levels in marine environments [ 9 ].…”