Advanced satellite technology and algorithms are making substantial progress in meeting the need for improved environmental monitoring of coastal waterways. Integrating high-resolution satellites with in-situ radiometric equipment is essential for effectively monitoring algal blooms and managing coastal resources. Our work has built a model to examine geographical and temporal fluctuations in chlorophyll-a concentration in Bushehr Bay, Persian Gulf, Iran, using radiometric data and high-resolution remote sensing. In this study, we used twenty-four bio-optical features for analysis. After evaluating and selecting the most important features, we used the top five features to estimate chlorophyll-a concentration using machine learning algorithms. Likewise, the model could effectively investigate our climatology of chlorophyll in the study area. Our findings provide a dependable approach to monitor the environmental effect of chlorophyll-a and enhance water quality and regional management of primary production in coastal waters. This proposed proxy may be implemented in comparable places globally.

中文翻译：

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波斯湾沿海浅水区水质调查


先进的卫星技术和算法在满足改进沿海水道环境监测的需求方面正在取得重大进展。将高分辨率卫星与原位辐射测量设备集成对于有效监测藻华和管理沿海资源至关重要。我们的工作建立了一个模型，使用辐射数据和高分辨率遥感来检查伊朗波斯湾布什尔湾叶绿素-a 浓度的地理和时间波动。在这项研究中，我们使用了 24 个生物光学特征进行分析。在评估和选择最重要的特征后，我们使用前五个特征通过机器学习算法估计叶绿素-a 浓度。同样，该模型可以有效地研究研究区域叶绿素的气候学。我们的研究结果为监测叶绿素-a 的环境影响和改善沿海水域水质和初级生产的区域管理提供了一种可靠的方法。这个提议的代理可以在全球类似的地方实施。