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

作　　者：Xiaopeng JIANG Zhiqiang GAO Zhicheng WANG 

机构地区：[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

出　　处：《Journal of Oceanology and Limnology》2024年第4期1216-1226,共11页海洋湖沼学报（英文）

基　　金：Supported by the Fundamental Research Projects of Science&Technology Innovation and Development Plan in Yantai City(No.2022JCYJ041);the Natural Science Foundation of Shandong Province(Nos.ZR2022MD042,ZR2022MD028);the Seed Project of Yantai Institute of Coastal Zone Research,Chinese Academy of Sciences(No.YICE351030601);the NSFC Fund Project(No.42206240)。

摘　　要：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.Re sults 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：green tide biomass estimation quantitative technique Yellow Sea unmanned aerial vehicle(UAV) remote sensing(RS) 

分 类 号：X87[环境科学与工程—环境工程] X834