Spatiotemporal dynamics of chlorophyll-a in Pekalongan coastal waters, Indonesia, derived from sentinel-2 imagery

IF 3.7 Q4 ENVIRONMENTAL SCIENCES
Muhammad Nur Al Fajrin, Lilik Maslukah, Aris Ismanto, Muhammad Zainuri, Anindya Wirasatriya, Ulung Jantama Wisha, Muhammad Shulhan Jihadi
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Abstract

Chlorophyll-a is a key indicator of primary productivity and an essential parameter for assessing estuarine water quality. This study developed an empirical algorithm for estimating chlorophyll-a concentration from Sentinel-2 imagery and investigated the influence of meteorological and hydrographic factors on chlorophyll-a variability in Pekalongan Waters, Central Java, Indonesia, during 2020–2024. In situ observations were conducted in the estuarine areas of the Mrican, Sengkarang, and Loji Rivers during the first transitional season and the Southeast Monsoon period. To minimize tidal effects, field sampling and satellite acquisition were performed under comparable tidal conditions (flood to ebb). Among the tested models, an exponential regression based on the green-to-red band ratio demonstrated the best performance (R2 = 0.543, RMSE = 1.284 µg/L, bias = 0.303 µg/L). The developed algorithm successfully captured the spatial distribution of chlorophyll-a, revealing consistently higher concentrations in estuarine areas (1.6–11.4 µg/L) than in offshore waters (0.2–7.0 µg/L), indicating strong terrestrial influence. Correlation analysis showed that chlorophyll-a concentration was negatively associated with wind speed (r = − 0.518) and sunshine duration (r = − 0.550), suggesting the influence of vertical mixing and light-related constraints on phytoplankton growth, whereas rainfall exhibited a strong positive relationship. River discharge showed only a moderate correlation, indicating that chlorophyll-a dynamics are controlled by multiple interacting environmental drivers. Overall, chlorophyll-a variability in Pekalongan Waters is shaped by the interaction of terrestrial inputs, meteorological forcing, and physical oceanographic processes. The proposed algorithm provides an effective approach for chlorophyll-a monitoring in tropical coastal waters.

基于sentinel-2卫星图像的印尼北卡隆岸沿海水域叶绿素a的时空动态
叶绿素a是初级生产力的重要指标,也是评价河口水质的重要参数。基于Sentinel-2遥感影像,开发了一种估算叶绿素-a浓度的经验算法,并研究了气象和水文因子对2020-2024年印尼中爪哇佩卡隆岸水域叶绿素-a变化的影响。在第一个过渡季和东南季候风期间,对美洲河、森卡朗河和洛吉河河口地区进行了现场观测。为了尽量减少潮汐的影响,在类似的潮汐条件下(从涨潮到退潮)进行了现场采样和卫星采集。其中,基于绿红波段比例的指数回归模型表现最佳(R2 = 0.543, RMSE = 1.284µg/L, bias = 0.303µg/L)。开发的算法成功捕获了叶绿素-a的空间分布,显示河口地区的浓度(1.6-11.4µg/L)始终高于近海地区(0.2-7.0µg/L),表明陆地影响强烈。相关分析表明,叶绿素-a浓度与风速(r = - 0.518)和日照时数(r = - 0.550)呈负相关,表明垂直混合和光照限制对浮游植物生长有影响,而降雨量对浮游植物生长有较强的正相关。河流流量仅表现出中等相关性,表明叶绿素-a动态受多种相互作用的环境驱动因素控制。总体而言,北卡隆岸水域的叶绿素-a变化是由陆地输入、气象强迫和海洋物理过程的相互作用形成的。该算法为热带沿海水域叶绿素-a的监测提供了有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.80
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