Estimation and verification of green tide biomass based on UAV remote sensing

Xiaopeng JIANG; Zhiqiang GAO; Zhicheng WANG

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Estimation and verification of green tide biomass based on UAV remote sensing

Ecology | Updated：2024-10-11

- Estimation and verification of green tide biomass based on UAV remote sensing
- Journal of Oceanology and Limnology Vol. 42, Issue 4, Pages: 1216-1226(2024)
- Affiliations：
  
  1.CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
  2.Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
  3.University of Chinese Academy of Sciences, Beijing 100049, China
- Author bio：
  
  zqgao@yic.ac.cn
- Funds：
- DOI：
  CLC：
- Received：12 June 2023，
  
  Online First：07 November 2023，
  
  Published：01 July 2024
- Accepted：
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JIANG Xiaopeng,GAO Zhiqiang,WANG Zhicheng.Estimation and verification of green tide biomass based on UAV remote sensing[J].Journal of Oceanology and Limnology,2024,42(04):1216-1226.
DOI：

JIANG Xiaopeng,GAO Zhiqiang,WANG Zhicheng.Estimation and verification of green tide biomass based on UAV remote sensing[J].Journal of Oceanology and Limnology,2024,42(04):1216-1226. DOI：

摘要

Abstract

Since 2007

the Yellow Sea green tide has broken out every summer

causing great harm to the environment and society. Although satellite remote sensing (RS) has been used in biomass research

there are several shortcomings

such as mixed pixels

atmospheric interference

and difficult field validation. The biomass of green tide has been lacking a high-precision estimation method. In this study

high-resolution unmanned aerial vehicle (UAV) RS was used to quantitatively map the biomass of green tides. By utilizing experimental data from previous studies

a robust relationship was established to link biomass to the red-green-blue floating algae index (RGB-FAI). Then

the lab-based model for green tide biomass from visible images taken by the UAV camera was developed and validated by field measurements. Results show that the accurate and cost-effective method is able to estimate the green tide biomass and its changes in given local waters of the near and far seas. The study provided an effective complement to the traditional satellite RS

as well as high-precision quantitative techniques for decision-making in disaster management.

关键词

Keywords

references

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Related Institution

University of Chinese Academy of Sciences

CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences

Laboratory for Marine Biology and Biotechnology, Pilot National Laboratory for Marine Science and Technology (Qingdao)

CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences

Laboratory of Marine Ecology and Environmental Science, Pilot National Laboratory for Marine Science and Technology(Qingdao)

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