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应用生态学报 ›› 2016, Vol. 27 ›› Issue (12): 3920-3926.doi: 10.13287/j.1001-9332.201612.006

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基于无人机遥感监测滩涂湿地入侵种互花米草植被覆盖度

周在明*, 杨燕明, 陈本清   

  1. 国家海洋局第三海洋研究所, 福建厦门 361005
  • 收稿日期:2016-04-05 出版日期:2016-12-18 发布日期:2016-12-18
  • 通讯作者: * E-mail: zhouzaiming@tio.org.cn
  • 作者简介:周在明,男,1980年生,助理研究员.主要从事海岸带资源环境研究. E-mail: tougaozhou@163.com
  • 基金资助:
    本文由福建省自然科学基金项目(2015J05085)、促进海峡两岸科技合作联合基金项目(U1405234)和国家海洋局第三海洋研究所基本科研业务费项目(HE150805-14B)资助

Fractional vegetation cover of invasive Spartina alterniflora in coastal wetland using unmanned aerial vehicle (UAV)remote sensing

ZHOU Zai-ming, YANG Yan-ming, CHEN Ben-qing   

  1. Third Institute of Oceanography, State Oceanic Administration, Xiamen 361005, Fujian, China
  • Received:2016-04-05 Online:2016-12-18 Published:2016-12-18
  • Contact: * E-mail: zhouzaiming@tio.org.cn
  • Supported by:
    This research was supported by the Natural Science Foundation of Fujian Province, China (2015J05085), the Science Foundation of Two Sides of the Strait (U1405234), and the Scientific Research Foundation of the Third Institute of Oceanography, State Oceanic Administration (HE150805-14B).

摘要: 为了实现对沿海滩涂湿地资源与生态环境的有效管理与利用,需要对区域内的入侵种互花米草进行高精度的监测与分析.本文以福建三沙湾为试验区,以低空无人机获取的可见光和多光谱影像为数据源,对互花米草植被覆盖度进行监测与分析,通过NDVI指数模型获取了多光谱影像的植被覆盖度信息,以可见光影像为参考进行了精度检验.结果表明: 影像区互花米草植被覆盖度以40%~60%和60%~80%的中高和高等级覆盖度为主.NDVI模型估算值与真实值之间的均方根误差RMSE为0.06,决定系数R2为0.92,两者具有较好的一致性.

Abstract: The effective management and utilization of resources and ecological environment of coastal wetland require investigation and analysis in high precision of the fractional vegetation cover of invasive species Spartina alterniflora. In this study, Sansha Bay was selected as the experimental region, and visible and multi-spectral images obtained by low-altitude UAV in the region were used to monitor the fractional vegetation cover of S. alterniflora. Fractional vegetation cover parameters in the multi-spectral images were then estimated by NDVI index model, and the accuracy was tested against visible images as references. Results showed that vegetation covers of S. alterniflora in the image area were mainly at medium high level (40%-60%) and high level (60%-80%). Root mean square error (RMSE) between the NDVI model estimation values and true values was 0.06, while the determination coefficient R2 was 0.92, indicating a good consistency between the estimation value and the true value.