• Spectroscopy and Spectral Analysis
  • Vol. 41, Issue 12, 3949 (2021)
Li-li YANG*, Zhen-peng WANG, and Cai-cong WU*;
Author Affiliations
  • College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
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    DOI: 10.3964/j.issn.1000-0593(2021)12-3949-08 Cite this Article
    Li-li YANG, Zhen-peng WANG, Cai-cong WU. Research on Large-Scale Monitoring of Spider Mite Infestation in Xinjiang Cotton Field Based on Multi-Source Data[J]. Spectroscopy and Spectral Analysis, 2021, 41(12): 3949 Copy Citation Text show less
    Images of cotton leaves with different degree of mite damage(a): Level 0; (b): Level 1; (c): Level 2; (d): Level 3
    Fig. 1. Images of cotton leaves with different degree of mite damage
    (a): Level 0; (b): Level 1; (c): Level 2; (d): Level 3
    Technical route of cotton field spider mite monitoring
    Fig. 2. Technical route of cotton field spider mite monitoring
    Spectral reflectance curves of ground canopies with different degrees of mite damage
    Fig. 3. Spectral reflectance curves of ground canopies with different degrees of mite damage
    First derivative spectral curve of ground canopy with the different degrees of spider mites damage
    Fig. 4. First derivative spectral curve of ground canopy with the different degrees of spider mites damage
    Reflectance curve of multispectral image with different degrees of spidermite damage
    Fig. 5. Reflectance curve of multispectral image with different degrees of spidermite damage
    Spatial distribution map (a, b, c, d, e, f) of cotton field spider mite monitoring in (June 22, 27, 28, Jule 3, 9, 13) different periods
    Fig. 6. Spatial distribution map (a, b, c, d, e, f) of cotton field spider mite monitoring in (June 22, 27, 28, Jule 3, 9, 13) different periods
    植被指数公式
    NDGI(G-R)/(G+R)
    TVI0.5×[120×(NIR-G)-200×(R-G)][10]
    MSR(NIR/R-1)/[(NIR/R)0.5+1][10]
    MSAVI0.5×{(2×NIR+1)-[(2×NIR+1)2-
    8×(NIR-R)]0.5}[11]
    RDVI(NIR-R)/[(NIR+R)0.5][10]
    RVINIR/R[11]
    REWDRVI(0.15×NIR-RE)/(0.15×NIR+RE)[11]
    DVINIR-R[10]
    GNDVI(NIR-G)/(NIR+G)[11]
    SAVI1.5×(NIR-R)/(NIR+R+0.5)[12]
    ARI(1/G)-(1/RE)
    OSAVI1.16×(NIR-R)/(NIR+R+0.16)[12]
    NDVI(NIR-R)/(NIR+R)[12]
    EVI2.5×[(NIR-R)/(NIR+6×R-7.5×G+1)][13]
    GRVINIR/G[13]
    GDVINIR-G[13]
    GOSAVI(1+0.16)×(NIR-G)/(NIR+G+0.16)[13]
    REDVINIR-RE[13]
    RERVINIR/RE[13]
    RESAVI1.5×[(NIR-RE)/(NIR+RE+0.5)][13]
    RERDVI(NIR-RE)/[(NIR+RE)0.5] [13]
    RENDVI(NIR-RE)/(NIR+RE)[13]
    REOSAVI(1+0.16)×(NIR-RE)/(NIR+RE+0.16)[13]
    Table 1. Calculation formulas for vegetation index
    植被指数RDVISAVIOSAVITVINDGIRVIMSR
    相关系数0.407*0.222**0.304**0.492**-0.304**0.210*0.197*
    Table 2. Correlation between the occurrence of spider mite and vegetation indices
    环境数据最高温度平均温度平均湿度温湿系数积温10 cm土壤最高温度10 cm土壤平均温度10 cm土壤平均湿度
    相关系数-0.218*-0.178*0.221**0.243**-0.213*-0.201*-0.258**0.213*
    Table 3. Correlation between the occurrence of spider mite and environmental data
    建模方式样本训练样本测试样本
    健康螨害准确率/%健康螨害准确率/%精确率/%召回率/%F1值/%
    单一环境数据M1健康
    螨害
    26
    9
    23
    32
    64.4413
    10
    8
    14
    6056.5261.959.09
    单一植被指数M2健康
    螨害
    27
    12
    9
    42
    76.6715
    8
    6
    16
    68.8965.2271.4368.18
    环境数据与植被
    指数结合M3
    健康
    螨害
    26
    3
    13
    48
    82.2212
    4
    5
    24
    807570.5972.73
    Table 4. Comparison of classification results of the different degrees of spider mite monitoring models
    环境数据最高温度平均湿度温湿系数积温10 cm土壤最高温度10 cm土壤平均温度
    相关系数0.707*0.844*0.931**0.837*0.856*0.974**
    Table 5. Correlation coefficient between environmental data and cotton field spider mite area
    模型RR2调整后R2标准估算的误差
    M20.8740.8480.8350.914 9
    Table 6. Model evaluation results
    日期实际值/亩预测值/亩
    6.2264.16858.374
    6.2718.36118.591
    6.2920.34818.101
    7.350.05541.666
    7.943.08742.39
    7.1372.83169.83
    Table 7. Comparison of prediction results of cotton field spider mite area prediction models
    Li-li YANG, Zhen-peng WANG, Cai-cong WU. Research on Large-Scale Monitoring of Spider Mite Infestation in Xinjiang Cotton Field Based on Multi-Source Data[J]. Spectroscopy and Spectral Analysis, 2021, 41(12): 3949
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