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

被引:0
|
作者
Xiaopeng JIANG [1 ,2 ]
Zhiqiang GAO [1 ,2 ]
Zhicheng WANG [1 ,2 ,3 ]
机构
[1] CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences
[2] Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences
[3] University of Chinese Academy of
关键词
D O I
暂无
中图分类号
学科分类号
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.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.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Estimation and verification of green tide biomass based on UAV remote sensing
    Jiang, Xiaopeng
    Gao, Zhiqiang
    Wang, Zhicheng
    [J]. JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2024, 42 (04) : 1216 - 1226
  • [2] UAV remote sensing based estimation of green cover during turfgrass establishment
    Wang, Tianyi
    Chandra, Ambika
    Jung, Jinha
    Chang, Anjin
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2022, 194
  • [3] Estimation of aboveground biomass of different vegetation types in mangrove forests based on UAV remote sensing
    Li, Shaorui
    Zhu, Zhenchang
    Deng, Weitang
    Zhu, Qin
    Xu, Zhihao
    Peng, Bo
    Guo, Fen
    Zhang, Yuan
    Yang, Zhifeng
    [J]. Sustainable Horizons, 2024, 11
  • [4] Remote sensing of the Yellow Sea green tide in 2014 based on GOCI
    Song, Debin
    Gao, Zhiqiang
    Xu, Fuxiang
    Zheng, Xiangyu
    Ai, Jinquan
    Chen, Maosi
    [J]. REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY XIV, 2017, 10405
  • [5] Analysis of the Impact of Green Tide on Aquaculture in Qingdao Based on Remote Sensing
    Jin, Xifang
    Huang, Juan
    Li, Xiaomin
    Zhang, Jie
    [J]. INFORMATION TECHNOLOGY FOR RISK ANALYSIS AND CRISIS RESPONSE, 2014, 102 : 730 - 736
  • [6] Estimation of Maize FPAR Based on UAV Multispectral Remote Sensing
    Wang, Laigang
    He, Jia
    Zheng, Guoqing
    Guo, Yan
    Zhang, Yan
    Zhang, Hongli
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2022, 53 (10): : 202 - 210
  • [7] The Detection of Green Tide Biomass by Remote Sensing Images and In Situ Measurement in the Yellow Sea of China
    Tian, Wei
    Wang, Juan
    Zhang, Fengli
    Liu, Xudong
    Yang, Jian
    Yuan, Junna
    Mi, Xiaofei
    Shao, Yun
    [J]. REMOTE SENSING, 2023, 15 (14)
  • [8] Estimation of Winter Rapeseed Above-ground Biomass Based on UAV Multi-spectral Remote Sensing
    Wang, Han
    Xiang, Youzhen
    Li, Wangyang
    Shi, Hongzhao
    Wang, Xin
    Zhao, Xiao
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2023, 54 (08): : 218 - 229
  • [9] Biomass Estimation: A Remote Sensing Approach
    Wei, Xiaofang
    [J]. GEOGRAPHY COMPASS, 2010, 4 (11): : 1635 - 1647
  • [10] The potential and challenge of remote sensing-based biomass estimation
    Lu, Dengsheng
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2006, 27 (07) : 1297 - 1328