A UAV and S2A data-based estimation of the initial biomass of green algae in the South Yellow Sea. (March 2018)

• Record Type: Journal Article
• Authors: Xu, Fuxiang; Gao, Zhiqiang; Jiang, Xiaopeng; Shang, Weitao; Ning, Jicai; Song, Debin; Ai, Jinquan
• Is Part Of: Marine pollution bulletin. Volume 128(2018)
• Page Start: 408
• Page End: 414
• Publication Date: 2018-03
• Subjects: Green algae -- Biomass -- UAV -- S2A -- Pyropia aquaculture raft -- Yellow Sea; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2018.01.061
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: Previous studies have shown that the initial biomass of green tide was the green algae attaching to Pyropia aquaculture rafts in the Southern Yellow Sea. In this study, the green algae was identified with unmanned aerial vehicle (UAV), an biomass estimation model was proposed for green algae biomass in the radial sand ridge area based on Sentinel-2A image (S2A) and UAV images. The result showed that the green algae was detected highly accurately with the normalized green-red difference index (NGRDI); approximately 1340 tons and 700 tons of green algae were attached to rafts and raft ropes respectively, and the lower biomass might be the main cause for the smaller scale of green tide in 2017. In addition, UAV play an important role in raft-attaching green algae monitoring and long-term research of its biomass would provide a scientific basis for the control and forecast of green tide in the Yellow Sea. Highlights: Raft-attaching green algae can be detected by NGRDI generated from UAV images. An initial biomass estimation model of green algae in the South Yellow Sea based UAV and S2A Data was proposed. Long-term initial biomass monitoring would provide a scientific basis for green tide control and forecast in the Yellow Sea.