Using Landsat 8 OLI data to differentiate Sargassum and Ulva prolifera blooms in the South Yellow Sea
Deyong Sun, Ying Chen, Shengqiang Wang, Hailong Zhang, Zhongfeng Qiu, Zhihua Mao, Yijun He
Abstract
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.