Identification of the mangrove species using UAV hyperspectral images: A case study of Zhangjiangkou mangrove national nature reserve

Zhou Zaiming; Chen Benqing; Xu Ran; Fang Wei

doi:10.12284/hyxb2021136

Volume 43 Issue 9

Sep. 2021

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Article Navigation > Haiyang Xuebao > 2021 > 43(9): 137-145

Zhou Zaiming，Chen Benqing，Xu Ran, et al. Identification of the mangrove species using UAV hyperspectral images: A case study of Zhangjiangkou mangrove national nature reserve[J]. Haiyang Xuebao，2021, 43(9)：137–145 doi: 10.12284/hyxb2021136

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Identification of the mangrove species using UAV hyperspectral images: A case study of Zhangjiangkou mangrove national nature reserve

doi: 10.12284/hyxb2021136

1.
Ocean Acoustics and Remote Sensing Laboratory, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
2.
Forestry College, Fujian Agriculture and Forestry University, Fuzhou 350002, China
3.
Zhangjiangkou Mangrove National Nature Reserve, Yunxiao 363000, China

Received Date: 2020-12-08
Rev Recd Date: 2021-05-06

Available Online: 2021-06-17

Publish Date: 2021-09-25

Abstract

Abstract

The composition and distribution of mangrove species are crucial to the protection and restoration of mangrove wetland ecosystems. In this study, mangrove species distribution was identified by unmanned aerial vehicle (UAV) hyperspectral images from Zhangjiangkou mangrove national nature reserve. Spectral characteristics, spectral differential, and spectral continuum removal were analyzed, 17 spectral parameters of 911 group spectral data from different vegetation species were obtained. Furthermore, 13 parameters for decision tree construction were selected by stepwise discriminant analysis. As a result, an accurate distribution map of mangrove species in the study area was obtained through C5.0 decision tree classification model. The vegetation species present different distribution types from top to bottom in the Zhangjiangkou mangrove national nature reserve. The upper part of the study area was dominated by the mixed type of Aegiceras corniculatum and Kandelia obovata. The middle area showed symbiosis status of three different mangrove species Avicennia marina, Aegiceras corniculatum and Kandelia obovata. The lower part of the study area was dominated by Avicennia marina, and a small amount of Kandelia obovata. Through the confusion matrix, the overall classification accuracy is 87.95% and the Kappa coefficient is 83.81%, showed a satisfactory precision. Therefore, our mangrove species identification results from UAV hyperspectral images could be used as a reference for ecological protection of regional mangrove wetland, and also as a identification method reference for mangrove species.
- mangrove,
- Zhangjiangkou,
- unmanned aerial vehicle (UAV),
- hyperspectral images,
- species identification

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