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 (300 mg/m³) in East Sea areas that typically have a relatively low total suspended particle concentration (<0.5 mg/m³).

准确及时地量化有害藻华的广泛分布（HAB），对于应对自然灾害，将破坏最小化并评估事件对环境的影响至关重要。尽管自海洋彩色卫星传感器问世以来，已经针对HAB提出了各种基于遥感的量化方法，但还没有针对朝鲜海中发生的赤潮进行现场定量测量验证的算法。此外，自地球静止海洋彩色成像仪（GOCI）在2010年6月问世以来，就迫切需要一种利用其空前的观测频率（白天的每个小时）的算法，以更好地跟踪赤潮的空间分布变化。Chl a）甲壳虫（Margalefidinium）polykrikoides（朝鲜海附近主要的赤潮物种之一）的浓度。这项开发的算法已使用在2013年8月进行的一次巡游活动中收集到的实测Chl a值进行了验证，当时大规模的C. polykrikoides盛开，摧毁了韩国沿海地区。所提出的算法 与原位Chl a测量结果具有高度相关性（R ² = 0.92），对于通常在总悬浮颗粒浓度相对较低的东海地区的高Chl a浓度（300 mg / m ³）也具有强大的性能（<0.5 mg / m ³）。