Spectroscopy and Spectral Analysis, Volume. 41, Issue 10, 3200(2021)
Detection of Pest Degree of Phyllostachys Chinese With Hyperspectral Data
Figures & Tables(13)
Fig. 3. Original spectra and the curves after removing the spectral envelopes of samples under different injury levels
Fig. 5. Spatial distribution of pest injury levels in sampling area
Table 1. Vegetation index and its calculation formula
View tableView in ArticleTable 1. Vegetation index and its calculation formula
植被指数 名称 计算公式 SAVI 土壤调节植被指数 1.5(ρ870-ρ680)/(ρ870+ρ680+0.5) PSNDa 归一化色素差值指数a (ρ800-ρ690)/(R800+ρ690) PSNDb 归一化色素差值指数b (ρ800-ρ635)/(ρ800+ρ635) mND705 修正归一化差值指数 (ρ750-ρ705)/(ρ750+ρ705-2ρ445) VOGa Vogelman指数a ρ740/ρ750 mSR705 改进比值植被指数 (ρ750-ρ445)/(ρ705+ρ445) DD 双重差异指数 (ρ750-ρ720)-(ρ700+ρ670) NDI 归一化差异指数 (ρ750-ρ705)/(ρ750+ρ705) GNDVI 绿光归一化植被指数 (ρ750-ρ550)/(ρ750+ρ550)
Table 2. Spectral characteristic parameters and its definitions
View tableView in ArticleTable 2. Spectral characteristic parameters and its definitions
参数 名称 定义 Depth560 绿峰吸收深度 在560 nm处的吸收深度 AreaG 绿峰吸收面积 在500~610 nm之间包络线与光谱反射率之间的面积 AreaR 红边吸收面积 在680~760 nm之间包络线与光谱反射率之间的面积 λR 红边位置 在680~760 nm之间反射率的一阶导数红边最大值位置 dλR 红边振幅 在680~760 nm之间反射率的一阶导数红边最大值 SDR 红边面积 在680~760 nm之间反射率的一阶导数红边面积 SDR-SDB 面积差值 红边面积与蓝边面积的差值
Table 3. Discriminant function based on the original spectrum
View tableView in ArticleTable 3. Discriminant function based on the original spectrum
函数 ρ400 ρ406 ρ586 ρ593 ρ689 ρ876 常数 方差/% y1 788.24 961.86 -382.94 422.87 -204.32 40.16 -5.71 89.3 y2 3721.39 -3461.94 -101.38 -109.92 74.46 5.53 -0.20 9.7 y3 -6028.94 6204.72 352.27 -646.97 222.93 4.72 -5.74 1.0
Table 4. Discriminant function based on the spectrum after removing the envelope
View tableView in ArticleTable 4. Discriminant function based on the spectrum after removing the envelope
函数 ρ403 ρ406 ρ409 ρ412 ρ505 ρ515 ρ735 ρ749 常数 方差/% y1 -113.40 -18.91 157.03 -49.78 -51.92 14.14 194.80 -376.44 239.65 88.3 y2 59.12 -262.44 82.09 99.94 -74.53 42.71 26.86 -5.17 18.74 9.1 y3 44.92 -162.80 -194.94 203.22 120.66 -78.28 -23.33 86.46 24.46 2.7
Table 5. Discriminant function based on canopy vegetation indexes
View tableView in ArticleTable 5. Discriminant function based on canopy vegetation indexes
函数 PSNDa PSNDb mND705 mSR705 NDI SAVI VOGa DD GNDVI 常数 方差/% y1 -32.64 -53.58 -764.78 -7.54 224.85 19.12 116.44 24.52 -1.15 -97.10 87.2 y2 -64.11 13.36 136.33 20.61 -162.59 -5.76 132.71 35.06 21.21 -127.46 11.0 y3 99.62 -71.51 121.12 9.22 -117.48 -34.92 140.24 -107.91 63.65 -189.80 1.8
Table 6. Discriminant function based on canopy spectral parameters
View tableView in ArticleTable 6. Discriminant function based on canopy spectral parameters
函数 Depth560 AreaR AreaG λR dλR SDR SDR-SDB 常数 方差/% y1 41.84 0.62 0.23 -68.53 0.03 228.59 -242.23 -82.95 84.0 y2 60.65 -0.23 0.79 1829.17 -0.15 -264.07 174.68 53.37 14.2 y3 156.17 0.10 1.84 -461.90 -0.08 324.33 -239.62 -122.10 1.8
Table 7. Different feature discriminant function accuracies
View tableView in ArticleTable 7. Different feature discriminant function accuracies
特征 检验精度/% Kappa
系数R2 健康 轻度 中度 重度 总体 原始光谱 92.0 73.3 82.4 84.8 84.4 0.79 0.89 去包络线 96.0 60.0 70.6 84.8 81.1 0.74 0.88 植被指数 96.0 73.3 70.6 78.8 79.7 0.74 0.88 光谱参数 92.0 73.3 64.7 84.8 78.7 0.76 0.85
Table 8. Test results of Phyllostachys Edulis Pest
View tableView in ArticleTable 8. Test results of Phyllostachys Edulis Pest
采样
区域健康 轻度虫害 中度虫害 重度虫害 总面积
/m2面积/m2 比例/% 面积/m2 比例/% 面积/m2 比例/% 面积/m2 比例/% 洋门A 222.16 2.32 1 395.09 14.56 2 530.45 26.41 5 432.30 56.70 9 580 洋门B 855.03 6.47 4 228.62 32.01 5 893.71 44.62 2 231.64 16.89 13 209 上湖A 4 815.13 43.89 2 004.44 18.27 3 410.13 31.09 740.30 6.75 10 970 上湖B 2 700.81 43.91 1 470.34 23.90 1 793.49 29.16 186.36 3.03 6 151
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. Detection of Pest Degree of Phyllostachys Chinese With Hyperspectral Data[J]. Spectroscopy and Spectral Analysis, 2021, 41(10): 3200
Paper Information
Category: Research Articles
Received: Oct. 7, 2020
Accepted: --
Published Online: Oct. 29, 2021
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