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全球水体藻类遥感识别研究进展

Progress in remote sensing identification of algal species in global water bodies

  • 摘要: 藻华会对公众健康、水生态安全及区域经济发展构成严重威胁,已成为全球性的水体生态环境问题。藻华成因复杂,不同藻类所引发的影响各异,其中藻类的种类及其优势种群是评估水体生态健康与安全的关键因素。传统实验室方法虽能提供高精度的藻类鉴定信息,但卫星遥感技术具备实时、大范围的观测优势,可实现全球水体藻类的动态监测。尽管已有研究利用遥感技术识别藻类,但其业务化应用仍面临诸多挑战。本文综述了藻类物种识别、特定藻类遥感监测及混合藻类区分等方面的研究进展。总体而言,卫星遥感已被证明能有效识别和监测不同门类的藻类,基于水体固有光学特性或表观光学特性的差异,已发展出多种藻类识别方法,但针对不同藻类种间差异的精细识别研究仍较为有限。进一步探究不同藻类的光学特性差异,是提升藻类识别效率的关键。未来藻类物种遥感识别研究将朝着算法精细化、藻类生物量定量反演、时空大尺度分析以及业务化应用等方向深入发展。本综述可为水环境监测、藻华预警与防控等相关研究提供参考。

     

    Abstract: Algal blooms pose a serious threat to public health, aquatic ecological security, regional economic development, and have become a global water ecological and environmental issue. The causes of algal blooms are complex, with different types of algae leading to varying impacts. Among these, the species of phytoplankton and their dominant populations are critical factors in assessing the ecological health and safety of water bodies. While traditional laboratory methods can provide high-precision algal identification information, satellite remote sensing technology offers the advantages of real-time and large-scale monitoring, enabling the dynamic observation of algae in global water bodies. Although existing studies have utilized remote sensing technology to identify algae, its operational application still faces numerous challenges. This article reviews the research progress in algal species identification, remote sensing monitoring of specific algae, and the differentiation of mixed algal species. Overall, satellite remote sensing has been proven effective in identifying and monitoring algae across different phyla. Based on differences in the inherent optical properties or apparent optical properties of water bodies, various algal identification methods have been developed. However, research on fine-scale identification of differences among various algal species remains relatively limited. Further investigation into the optical property differences among different algae is key to improving algal identification efficiency. Future research on remote sensing identification of algal species will advance in the directions of refined algorithms, quantitative inversion of algal biomass, large-scale spatiotemporal analysis, and operational applications. This review aims to provide references for related studies in water environment monitoring, algal bloom early warning, and prevention and control.

     

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