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<p>Coral reefs, acknowledged as productive marine ecosystems, are increasingly threatened by bacterial infections that lead to the rapid degradation of these essential structures. While bleaching and thermal stress have been extensively studied via satellite observations, the analysis of bacterial infections in relation to remote sensing applications remains insufficiently addressed. Addressing this knowledge gap is essential for improving reef health assessment and, in turn, supporting earlier detection of disease-related stress signals inferred from remotely sensed optical and environmental indicators in coral reef ecosystems. This review integrates remote sensing technologies with microbiological insights to detect and monitor coral disease manifestations associated with bacterial infections in the Red Sea. Remote sensing has become an essential method for the thorough and economical observation of coral reef ecosystems. This paper consolidates the use of spectral indices, hyperspectral sensors, and data acquired from Landsat, Sentinel-2, and unmanned aerial vehicles (UAVs) for identifying alterations in coral health. The amalgamation of field microbiological surveys with satellite imagery improves the accuracy of disease mapping and enables spatial modeling of infection dynamics. The main challenges include limited spatial resolution, interference from the water column, and spectral overlaps among various states of coral health. Spectral overlap transpires when reflectance signals from several coral health conditions—such as bacterial infection, bleaching, or algae overgrowth—coalesce, hence confounding disease differentiation. Detection is limited by sensor spatial resolution, which varies from 30&#xa0;m (Landsat-8) and 10–20&#xa0;m (Sentinel-2) to 1–2&#xa0;m (WorldView) and less than 1&#xa0;m for UAV or airborne sensors. Innovative technologies such as high-resolution hyperspectral sensors, Light Detection and Ranging (LiDAR), Synthetic Aperture Radar (SAR), and Artificial Intelligence (AI)-based classification exhibit considerable potential to overcome existing limitations and enhance disease prediction capabilities. The integration of microbial ecology and sophisticated remote sensing provides a comprehensive framework for the early diagnosis and ongoing monitoring of coral diseases. This multidisciplinary approach strengthens predictive modeling, facilitates adaptive management, and optimizes conservation measures. Future research should focus on advancing spatiotemporal monitoring systems, validating AI-driven prediction models, and executing next-generation hyperspectral missions in various reef ecosystems.</p>

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Detection of bacterial coral reef diseases in the Red Sea: a review of advances in remote sensing and microbiological approaches

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月15日

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  • Ahmed M. Khalifa,
  • Moaz M. Hamed,
  • Mostafa A. Khaled,
  • Khaled Z. ElBaghdady

摘要

Coral reefs, acknowledged as productive marine ecosystems, are increasingly threatened by bacterial infections that lead to the rapid degradation of these essential structures. While bleaching and thermal stress have been extensively studied via satellite observations, the analysis of bacterial infections in relation to remote sensing applications remains insufficiently addressed. Addressing this knowledge gap is essential for improving reef health assessment and, in turn, supporting earlier detection of disease-related stress signals inferred from remotely sensed optical and environmental indicators in coral reef ecosystems. This review integrates remote sensing technologies with microbiological insights to detect and monitor coral disease manifestations associated with bacterial infections in the Red Sea. Remote sensing has become an essential method for the thorough and economical observation of coral reef ecosystems. This paper consolidates the use of spectral indices, hyperspectral sensors, and data acquired from Landsat, Sentinel-2, and unmanned aerial vehicles (UAVs) for identifying alterations in coral health. The amalgamation of field microbiological surveys with satellite imagery improves the accuracy of disease mapping and enables spatial modeling of infection dynamics. The main challenges include limited spatial resolution, interference from the water column, and spectral overlaps among various states of coral health. Spectral overlap transpires when reflectance signals from several coral health conditions—such as bacterial infection, bleaching, or algae overgrowth—coalesce, hence confounding disease differentiation. Detection is limited by sensor spatial resolution, which varies from 30 m (Landsat-8) and 10–20 m (Sentinel-2) to 1–2 m (WorldView) and less than 1 m for UAV or airborne sensors. Innovative technologies such as high-resolution hyperspectral sensors, Light Detection and Ranging (LiDAR), Synthetic Aperture Radar (SAR), and Artificial Intelligence (AI)-based classification exhibit considerable potential to overcome existing limitations and enhance disease prediction capabilities. The integration of microbial ecology and sophisticated remote sensing provides a comprehensive framework for the early diagnosis and ongoing monitoring of coral diseases. This multidisciplinary approach strengthens predictive modeling, facilitates adaptive management, and optimizes conservation measures. Future research should focus on advancing spatiotemporal monitoring systems, validating AI-driven prediction models, and executing next-generation hyperspectral missions in various reef ecosystems.