A novel remote sensing algorithm was developed based on Landsat 8 Operational Land Imager (OLI) data to separately recognize concurrent Sargassum and Ulva prolifera in the South Yellow Sea. This algorithm has three main steps: 1) classification of macroalgae-containing pixels from normal seawater pixels by means of a mature floating algae index (FAI) approach; 2) first-round separate recognition of the Sargassum and Ulva prolifera targets using a newly developed “Sargassum and Ulva prolifera Index I (SUI-I)” method; and 3) further fine identification of the algae by applying another new index (SUI-II) to the above output. The validation of our developed algorithm generated high and satisfactory predictive accuracies. The present study concludes that the Landsat 8 OLI data have great potential for detecting and distinguishing the mixed growth of Sargassum and Ulva prolifera, which will help in closely monitoring macroalgae blooms in oceanic waters.

基于Landsat 8 Operational Land Imager（OLI）数据，开发了一种新颖的遥感算法，以分别识别南黄海中并发的Sargassum和Ulva增殖。该算法具有三个主要步骤：1）通过成熟的浮藻指数（FAI）方法将正常海水像素中的含巨藻像素分类。2）使用新开发的“ Sargassum和Ulva prolifera ”对轮虫和Ulva增殖目标进行第一轮单独识别索引I（SUI-I）”方法；3）通过对上述输出应用另一个新索引（SUI-II），进一步细化藻类。我们开发的算法的验证产生了较高且令人满意的预测准确性。本研究的结论是，Landsat 8 OLI数据具有检测和区分Sargassum和Ulva prolifera混合生长的巨大潜力，这将有助于密切监视海洋水域中的大型藻类开花。