摘　要：绿潮是我国近海常见的一种海洋生态灾害。为利用无人机（UAV）RGB光学相机准确高效地监测绿潮，建立高分辨率RGB光学影像中绿藻快速提取算法，本文提出了一种新的指数用于增强漂浮绿藻的信号，即以绿色和红色波段形成一个虚拟基线，此基线以下蓝波段信号的线高即为红绿波段虚拟基线漂浮绿藻指数（RG-FAH）。此外，利用不同条件的无人机影像与其他植被指数对比进行验证。试验结果表明，RG-FAH在不同条件下的准确率、kappa等指标都在0.91以上。在正常与过曝光的条件下及提取大面积绿藻斑块时，RG-FAH与绿波段和蓝波段的差值（GB）相当，但在太阳耀光耐受性和小斑块提取方面比GB及其他指数表现更好。该RG-FAH指数在绿藻及类似的水体漂浮绿色植物的监测方面有应用潜力，能为绿潮的监测、管理提供有效的信息支持。
关键词：绿藻监测；UAV；光学影像；植被指数；虚拟基线
中图分类号：P407.8　　　　　　文献标志码：ADOI：10.3969/j.issn.1007-7146.2021.04.004

Abstract: Green tide is a common marine ecological disaster in offshore China. In order to use the UAV RGB optical camera to accurately monitor the green tide and establish a fast extraction index for green algae in high-resolution RGB optical images. A new index is proposed to enhance the signal of floating green algae. A virtual baseline is formed in the green and red bands, and the line-height of the blue band signal under this virtual baseline is the red-green band virtual baseline floating green algae index (RG-FAH). In addition, representative UAV images under different conditions are used to compare with other vegetation indices for verification. The experimental results show that the accuracy and kappa of RG-FAH under different conditions are all above 0.91. Under normal and overexposure conditions and the extraction of large patches of algae, RG-FAH appears to be comparable to GB, yet it is more beneficial than GB and other indices in terms of sun glitter tolerance and small patches of algae extraction. The RG-FAH index proposed in this study has potential application value in monitoring green algae and similar floating green plants in seawater. It can also provide effective information support for the monitoring and management of green tide.
Key words: green tide; UAV; optical images; vegetation indices; virtual baseline
（Acta Laser Biology Sinica, 2021, 30(4): 316-324）