Scholarlink

<p>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 (R<sup>2</sup> = 0.543, RMSE = 1.284&#xa0;µg/L, bias = 0.303&#xa0;µg/L). The developed algorithm successfully captured the spatial distribution of chlorophyll-a, revealing consistently higher concentrations in estuarine areas (1.6–11.4&#xa0;µg/L) than in offshore waters (0.2–7.0&#xa0;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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月10日

查看全文
  • Muhammad Nur Al Fajrin,
  • Lilik Maslukah,
  • Aris Ismanto,
  • Muhammad Zainuri,
  • Anindya Wirasatriya,
  • Ulung Jantama Wisha,
  • Muhammad Shulhan Jihadi

摘要

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.