Remote sensing methods for biomass estimation of green algae attached to nursery-nets and raft rope

MARINE POLLUTION BULLETIN

卷:150

Article

Jiang, Xiaopeng^1,3  Gao, Zhiqiang¹  Zhang, Qingchun^2,4,5  Wang, Yueqi¹  Tian, Xinpeng¹  Shang, Weitao^1,3  Xu, Fuxiang⁶ 

[1] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China

[2] Chinese Acad Sci, Inst Oceanol, CAS Key Lab Marine Ecol & Environm Sci, Qingdao 266071, Peoples R China

[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[4] Qingdao Natl Lab Marine Sci & Technol, Lab Marine Ecol & Environm Sci, Qingdao 266071, Peoples R China

[5] Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China

[6] Shandong Technol & Business Univ, Sch Publ Adm, Yantai 264005, Peoples R China

关键词: Green tide;    Biomass estimation;    Unmanned aerial vehicle;    Attached algae;    Subei shoal;   

DOI  :  10.1016/j.marpolbul.2019.110678

来源: Elsevier

【 摘 要 】

Accurate estimation of the biomass of raft-attached green algae is important for predicting the scale of green-tides in the Yellow Sea, China. In this study, two different biomass estimation methods are proposed: green algae attached to nursery-net (GAAN) and green algae attached to rope (GAAR). The GAAN method involves the use of images obtained using an unmanned aerial vehicle (UAV), high-resolution satellite images, and data from a statistical yearbook. The GAAR method uses high-resolution satellite images and data from a field sample survey. The results showed that the biomass of GAAN and GAAR in the Subei Shoal during 2017 was 8868 tons and 2974 tons respectively. A longer-term study of the biomass of GAAN and GAAR could provide quantitative information for the earnings forecasts of Porphyra yezoensis and for green-tide prevention.

【 授权许可】

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