# Monitoring and Forecasting Green Tide in the Yellow Sea Using Satellite Imagery
## 1 Introduction  
Green tide, an ecological anomaly formed by the explosive growth and aggregation of macroalgae in the ocean, is common in coastal countries around the world [1; 2]. The green tide in the Yellow Sea is one of the largest green tide events in the world; it has been occurring annually for 15 years, lasts for a long time every year, affects a wide area of the sea, and is difficult to clean up [3; 4; 5; 6]. It has a significant negative impact on the local marine ecosystem and coastal economy, and it is relatively tolerant to high temperatures and light intensity [8], so it is highly persistent with explosive growth and has gradually become a regular marine ecological hazard. Therefore, there is an urgent need for effective dynamic monitoring of the green tide to guide prevention and control measures. Compared with field surveys, satellite remote sensing (RS) has the advantages of a wide monitoring area, fast information acquisition, a short update period, timeliness, and strong economic benefits and is thus an effective means of real-time monitoring and control of green tide events [9; 10]. The green tide index threshold method based on RS, which follows the principle that green algae have unique spectral characteristics in the visible and infrared bands, has been widely used to extract green tide information and is no longer limited by the type of satellite sensor. For example, various green tide index threshold methods based on band calculation, such as the normalized vegetation index [11], theenhanced vegetation index (EVI, a MOD13 satellite-derived index), and the normalized difference algal index [12]. Moreover, there are other methods based on baseline subtraction that are less sensitive to changes in environmental and observation conditions, and can extract green tide information through thin clouds [9; 13], such as baseline-based floating algae index [14], virtual-baseline drifting algae indices [15], and the RGB floating algae index [16]. All of these indices are widely used as they can clarify the differences between seawater and green tide features. Although the index calculation method and principle for green tide have been improved, optimization of the threshold selection method is still far from adequate; continuous refinement and improvement from a manual empirical judgment to a more automatic threshold selection are needed to improve the efficiency of green tide extraction and the dynamic monitoring capability of RS. Thus, one of the purposes of this study is to propose an effective, universal, and more automatic method for extracting green tide from RS images. Since 2007, major green tide events have occurred in the Yellow Sea from March to August of each year. Since the first outbreak of this green tide, early prevention and control have been key concerns, and the tracing of the source of the Yellow Sea green tide is of utmost importance. RS satellite monitoring is the most common and effective means to trace the green tide. According to previous studies, the Subei shool along the Jiangsu coast is considered to be the direct origin of the Yellow Sea green tide outbreak, as local geographical, aquaculture, and biological factors provide sufficient nutrients and a suitable growth environment for the green algae [1; 3; 4; 13]. Further, morphological and phylogenetic analyses have shown that this green tide is homologous to the algal species in the purslane culture area of Jiangsu [17]. Consistently, RS satellite monitoring and field surveys have demonstrated that most of the initial discovery sites of the Yellow Sea green tide were also near the layer farms in the Subei shool along the Jiangsu coast [1; 3; 4; 13]. Therefore, evidence from various sources in previous studies has indicated that the Subei shool along the Jiangsu coast is the source of the Yellow Sea green tide. At the same time, the current traceability of the Yellow Sea green tide source, whether by RS monitoring or field investigation, is limited to the Subei shool.