## 5 Conclusions  
The world's largest macroalgal blooms have appeared in the Yellow Sea every summer since 2007, becoming a tricky, complicated, and repetitive issue for the marine environment. In this study, the NDVI index was used to extract information about the green tide from MODIS images during 2016-2018. Along with the overall morphology, the morphological characteristics of the _U. prolifera_ distribution were analyzed. The conclusions were as follows:  
Figure 17: Three-day average surface wind speed and direction of oblateness change periods in 2017, obtained from RSS. (**a-c**) The change of SSW in period one. (**d**,**e**) The change of SSW in period two. Figure 18: Three-day average surface wind speed and direction of oblateness change periods in 2016, obtained from RSS. (**a-c**) The change of SSW in period one. (**d**,**e**) The change of SSW in period two. * In recent years, the overall _U. prolifera_ situation was still severe, with the largest distribution and coverage areas reaching 57,384 km\({}^{2}\) and 2906 km\({}^{2}\) on 25 June 2016. The growth pattern of _U. prolifera_ has changed greatly in three years: in 2016, the growth of _U. prolifera_ was basically in line with the five stages of previous years; in 2017, two peaks appeared in different time periods and different locations; in 2018, _U. prolifera_ entered a month-long stable period, during which the center of gravity shifted significantly. In 2016, the largest scale occurred, and in 2017, the longest migration path was experienced. In contrast, the situation of _U. prolifera_ in 2018 has been alleviated to a certain extent. Continuous monitoring of _U. prolifera_ is conducive to obtaining a deep understanding of its growth cycle, grasping the changes in its development from year to year, and reassessing the severity of the green tide event. * The total affected region was 163,162 km\({}^{2}\), of which the high-risk areas (with a probability of occurrence greater than 50%) were concentrated mainly in the small sea area near Qingdao. This finding provided a reference for manpower and resource allocation in preventing and treating this severe marine ecological problem. * The trend of the migration track was basically consistent within these three years. _U. prolifera_ drifted northwest, and finally died out in the sea area near Qingdao, Shandong Province. Representing the concentration point of the density, the center of gravity of _U. prolifera_ goes hand in hand with its distribution. The migration of the barycenter is the basis of the growth prediction model, which is helpful in achieving the sub-regional and sub-period management of _U. prolifera_. * The regularity of the boundary shape of the _U. prolifera_ distribution showed an opposite change pattern to its scale variation. In most instances, the wider the distribution area, the more regular the shape and the denser were the algae, a finding that was beneficial for large-scale centralized management. On the contrary, when the distribution area was small, the shape of the boundary was variable, and collective salvage was not achievable. * Changes in SSW in direction and speed were the main causes of _U. prolifera_ migration, and they also accounted for changes in its distribution morphology. The relationship between SSW and the morphology parameters was conducive to optimizing and improving the _U. prolifera_ prediction model. In addition to predicting the occurrence position of the green tide based on its center of gravity drift path, the distribution, direction, and scale of macroalgae blooms were further specified by using morphological parameters. Monitoring _U. prolifera_ development should be an ongoing project. Although the findings presented here can be explained by the SSW, they are preliminary in nature. Quantitative analysis of the correlation between SSW, _U. prolifera_ drift, and morphological changes, leading to early warnings and the prediction of green tide events, will become the focus of future research. Conceptualization, Y.W., Y.C. and Z.F. ; methodology, Y.W.