Since 2008, macroalgal blooms of Ulva Prolifera (also called green tide) have occurred every summer in the Yellow Sea (YS), which has caused environmental and economic problems. In recent years, a variety of detection algorithms for green tide have been proposed. However, the extraction thresholds of each algorithm are uncertain because of atmospheric conditions, the distribution of green tides, etc. In this paper, Geostationary Ocean Color Imager (GOCI) data and Landsat- 8 data were used to explore the threshold stability of some common detection algorithms for green tide, including the AFAI, DVI, EVI, IGAG, and NDVI. Four scenes of GOCI satellite data from 2016 to 2018 were selected for the experiments. The first step was to extract the green tide areas in one region to determine the threshold for each algorithm. In this step, the extraction results of the Landsat-8 data, which has a resolution of 30 m, was seen as the true value of the green tide coverage. Then, we determined the threshold value for each algorithm by visual inspection. The thresholds determined in the first step were used to extract the green tide area in the other three regions, and the extraction results were compared by visual contrast. A comparison of the extraction precision for each algorithm in the other three regions indicated that the threshold stability of the AFAI algorithm was the best among these data in the YS region.
In recent years, blooms of Sargassum horneri have occurred frequently in the Yellow Sea and the East China Sea. Optical satellite remote sensing is an important means to monitor Sargassum horneri, the method being based mainly on exploiting the significant spectral differences between the water mixed with Sargassum horneri and the background seawater. Thus, it is necessary to study the spectral characteristics of Sargassum horneri in seawater with a view to improving measurement accuracy. To date, both laboratory-based experiments concerning the spectral characteristics of Sargassum horneri as well as satellite-based remote sensing monitoring have been performed, but these studies have focused mainly on large areas of Sargassum horneri, and there has been limited recognition of the differences in the spectral characteristics for situations where the Sargassum horneri outbreak is early, and where the Sargassum horneri and the background seawater have just mixed. In this study, experiments have been designed to carefully examine the spectral characteristics of Sargassum horneri in seawater.
The main findings are: (1) In general, the spectral distribution for the two forms of Sargassum (the strip form and the uniformly distributed form) are similar. (2) The peak wavelengths for the two forms of Sargassum horneri in seawater are different. The peak maximum for the strip form is at 825 nm while that for the uniformly distributed form is at 725 nm. Thus, spectral measurements may be used to distinguish between the two forms. (3) The concentration of suspended matter in the background seawater may influence the spectral characteristics of Sargassum horneri in seawater. These findings have great significance for remote sensing of the mixed state of Sargassum horneri in seawater, namely, the possibility for differentiation of the uniformly distributed form and strip distribution form. Also, the results have important implications for remote sensing of Sargassum horneri in seawater where the concentrations of suspended matter are variable.
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