The East China Sea (ECS) has experienced severe harmful algal blooms (HABs) that have deleterious ecological effects on marine organisms. Recent studies indicated that deploying of a second geostationary ocean color imager (GOCI-II) can significantly improve ocean monitoring. This study systematically assessed GOCI-II and its ability to detect HABs and distinguish between dinoflagellates and diatoms in the ECS. First, the remote-sensing reflectance ( $${R}_{rs}\left(\lambda \right),$$ $$\lambda$$ represents the wavelength) obtained from GOCI-II was compared to the local measurement data. Compared to the bands at 412 and 443 nm, the bands at 490, 510, and 620 nm exhibited excellent consistency, which is important for HAB detection. Second, four different methods were employed to extract bloom areas in the ECS: red tide index (RI), spectral shape (SS), red band line height ratio (LHR), and algal bloom ratio ( $${R}_{AB}$$ ). The SS (510) algorithm was the most applicable for detecting blooms from GOCI-II imagery. Finally, the classification capability of GOCI-II for dinoflagellates and diatoms was evaluated using three existing algorithms: the bloom index (BI), combined $$Prorocentrum donghaiens$$ index (PDI) and diatom index (DI), and the spectral slope ( $${R}_{\_slope}$$ ). The BI algorithm yielded more satisfactory results than the other algorithms.

中文翻译：

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使用 GOCI-II 图像检测东海有害藻华

东海（ECS）经历了严重的有害藻华（HAB），对海洋生物产生了有害的生态影响。最近的研究表明，部署第二个对地静止海洋彩色成像仪（GOCI-II）可以显着改善海洋监测。本研究系统地评估了 GOCI-II 及其检测 HAB 和区分 ECS 中甲藻和硅藻的能力。首先，将GOCI-II获得的遥感反射率（$${R}_{rs}\left(\lambda\right),$$$$\lambda$$表示波长）与本地测量数据进行比较。与412和443 nm处的条带相比，490、510和620 nm处的条带表现出优异的一致性，这对于HAB检测很重要。其次，采用四种不同的方法来提取ECS中的水华区域：赤潮指数（RI）、光谱形状（SS）、红带线高比（LHR）和藻华比例（$${R}_{AB }$$）。SS (510) 算法最适用于检测 GOCI-II 图像中的水华。最后，使用三种现有算法评估了 GOCI-II 对甲藻和硅藻的分类能力：水华指数 (BI)、组合 $$Prorocentrum donghaiens$$ 指数 (PDI) 和硅藻指数 (DI) 以及光谱斜率 ( $${R}_{\_坡度}$$ )。BI 算法比其他算法产生了更令人满意的结果。