| 来源类型 | Article
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| 规范类型 | 其他
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| DOI | 10.3390/f9030115
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| Hyperspectral Analysis of Pine Wilt Disease to Determine an Optimal Detection Index. |
| Kim S-R; Lee W-K; Lim C-H; Kim M; Kafatos M; Lee S-H; Lee S-S
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| 发表日期 | 2018
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| 出处 | Forests 9 (3): e115
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| 出版年 | 2018
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| 语种 | 英语
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| 摘要 | Bursaphelenchus xylophilus, the pine wood nematode (PWN) which causes pine wilt disease, is currently a serious problem in East Asia, including in Japan, Korea, and China. This paper investigates the hyperspectral analysis of pine wilt disease to determine the optimal detection indices for measuring changes in the spectral reflectance characteristics and leaf reflectance in the Pinus thunbergii (black pine) forest on Geoje Island, South Korea. In the present study, we collected the leaf reflectance spectra of pine trees infected with pine wilt disease using a hyperspectrometer. We used 10 existing vegetation indices (based on hyperspectral data) and introduced the green-red spectral area index (GRSAI). We made comparisons between non-infected and infected trees over time. A t-test was then performed to find the most appropriate index for detecting pine wilt disease-infected pine trees. Our main result is that, in most of the infected trees, the reflectance changed in the red and mid-infrared wavelengths within two months after pine wilt infection. The vegetation atmospherically resistant index (VARI), vegetation index green (VIgreen), normalized wilt index (NWI), and GRSAI indices detected pine wilt disease infection faster than the other indices used. Importantly, the GRSAI results showed less variability than the results of the other indices. This optimal index for detecting pine wilt disease is generated by combining red and green wavelength bands. These results are expected to be useful in the early detection of pine wilt disease-infected trees. |
| 主题 | Ecosystems Services and Management (ESM)
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| 关键词 | GRSAI, Pine wilt disease, Remote sensing pine wood nematode, Spectrometer, Vegetation index
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| URL | http://pure.iiasa.ac.at/id/eprint/15162/
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| 来源智库 | International Institute for Applied Systems Analysis (Austria)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/131268
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推荐引用方式
GB/T 7714 |
Kim S-R,Lee W-K,Lim C-H,et al. Hyperspectral Analysis of Pine Wilt Disease to Determine an Optimal Detection Index.. 2018.
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文件名：
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forests-09-00115.pdf
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格式：
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Adobe PDF
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