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<p>Chlorophyll-a (Chl-a) concentration measures the green pigment in phytoplankton, which affects global ecosystems and is influenced by climate change and human activities. Monitoring chlorophyll-a (Chl-a) in oceans and lakes is challenging due to factors such as assessment techniques and prediction accuracy. This paper conducts a meta-analysis of recent techniques employed in monitoring, estimating, modeling, and predicting oceanic/lake Chl-a concentrations, considering spatio-temporal perspectives and utilizing diverse datasets. The analysis was conducted at two spatial scales (local and global) to evaluate how recent methods have advanced the understanding of Chl-a concentration assessment (CCA). According to the analysis, approximately 45% of Chl-a research originates from developed countries, while 55% is conducted in emerging countries. This study identified several research gaps: (a) Limited use of publicly available satellite data, with Landsat (10%) and Sentinel (12%) studies restricted to local scales, not global. (b) Major seas lack adequate coverage for Chl-a estimation. (c) Models are not sophisticated enough, often ignoring key factors. While temperature (39%) and nutrient availability (29%) are recognized as primary regulators, factors such as light, turbidity, currents, mixing, and stratification are frequently overlooked. As a key contribution, this review synthesizes various data types, quantitative techniques, and influencing factors in Chl-a concentration mapping across scales, highlighting its complexities, benefits, and recent spatio-temporal advancements over traditional approaches.</p>

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Current and emerging techniques for oceanic and lake chlorophyll-a estimation and monitoring: a global perspective

  • 期刊论文

  • 发表日期：

    2026年3月6日

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  • Ratiranjan Jena,
  • Abdallah Shanableh,
  • Rami Al-Ruzouq,
  • Mohammed Barakat A. Gibril,
  • Nezar Atalla Hammouri,
  • Fatema Habib Farweh,
  • Ahmad Ghassan Shabib,
  • Omid Ghorbonzadeh

摘要

Chlorophyll-a (Chl-a) concentration measures the green pigment in phytoplankton, which affects global ecosystems and is influenced by climate change and human activities. Monitoring chlorophyll-a (Chl-a) in oceans and lakes is challenging due to factors such as assessment techniques and prediction accuracy. This paper conducts a meta-analysis of recent techniques employed in monitoring, estimating, modeling, and predicting oceanic/lake Chl-a concentrations, considering spatio-temporal perspectives and utilizing diverse datasets. The analysis was conducted at two spatial scales (local and global) to evaluate how recent methods have advanced the understanding of Chl-a concentration assessment (CCA). According to the analysis, approximately 45% of Chl-a research originates from developed countries, while 55% is conducted in emerging countries. This study identified several research gaps: (a) Limited use of publicly available satellite data, with Landsat (10%) and Sentinel (12%) studies restricted to local scales, not global. (b) Major seas lack adequate coverage for Chl-a estimation. (c) Models are not sophisticated enough, often ignoring key factors. While temperature (39%) and nutrient availability (29%) are recognized as primary regulators, factors such as light, turbidity, currents, mixing, and stratification are frequently overlooked. As a key contribution, this review synthesizes various data types, quantitative techniques, and influencing factors in Chl-a concentration mapping across scales, highlighting its complexities, benefits, and recent spatio-temporal advancements over traditional approaches.