• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 4, 1278 (2022)
Maiming Yumiti* and Xue-mei WANG1; 2; *;
Author Affiliations
  • 1. College of Geographic Science and Tourism, Xinjiang Normal University, Urumqi 830054, China
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    DOI: 10.3964/j.issn.1000-0593(2022)04-1278-07 Cite this Article
    Maiming Yumiti, Xue-mei WANG. Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1278 Copy Citation Text show less
    Distribution of sampling points
    Fig. 1. Distribution of sampling points
    Spectral curves of organic matter content in different grades
    Fig. 2. Spectral curves of organic matter content in different grades
    Correlation analysis of soil organic matter content with reflectance spectra and spectral transformations
    Fig. 3. Correlation analysis of soil organic matter content with reflectance spectra and spectral transformations
    The correlation between soil organic matter content and wavelet coefficients
    Fig. 4. The correlation between soil organic matter content and wavelet coefficients
    Comparison of measured and estimated values of soil organic matter content using CWT
    Fig. 5. Comparison of measured and estimated values of soil organic matter content using CWT
    样品类型样品数
    /个
    有机质含量/(g·kg-1)变异系
    数/%
    最大值最小值平均值标准差
    总体样品9817.5821.1508.5743.58941.86
    Table 1. Basic statistical characteristics of soil samples
    光谱变换特征波
    段数量
    对应波段范围/nm显著性水平
    (p值)
    R1 135529933, 2 3512 382<0.01
    lg(1/R)1 137526934, 2 3492 378<0.01
    R'318431538, 800889,
    1 4511 660, 1 9742 035
    <0.01
    [lg(1/R)]'293431538, 795881,
    1 7312 042
    <0.01
    Table 2. The characteristic bands selected by different transformations
    模型建模集验证集RPD
    R2RMSER2RMSE
    R-PLSR0.592.290.462.961.55
    R-SVMR0.612.900.322.921.23
    lg(1/R)-PSLR0.582.310.462.641.54
    lg(1/R)-SVMR0.632.230.312.991.60
    R'-PSLR0.612.240.462.641.59
    R'-SVMR0.692.050.482.591.74
    [lg(1/R)]'-PLSR0.612.230.462.621.60
    [lg(1/R)]'-SVMR0.721.930.532.441.85
    R-CWT-21-PLSR0.682.020.462.631.77
    R-CWT-21-SVMR0.791.680.522.481.92
    R-CWT-22-PLSR0.612.230.482.641.72
    R-CWT-22-SVMR0.821.560.562.381.98
    R-CWT-23-PLSR0.632.180.462.621.73
    R-CWT-23-SVMR0.841.490.532.382.11
    R-CWT-24-PLSR0.652.110.522.571.86
    R-CWT-24-SVMR0.871.370.502.441.91
    R-CWT-25-PLSR0.652.110.552.401.89
    R-CWT-25-SVMR0.851.440.472.531.99
    R-CWT-26-PLSR0.652.120.562.391.88
    R-CWT-26-SVMR0.851.450.502.531.86
    R-CWT-27-PLSR0.602.250.512.501.58
    R-CWT-27-SWMR0.801.640.412.741.97
    Table 3. Inversion results of modeling set and validation set for soil organic matter content
    Maiming Yumiti, Xue-mei WANG. Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1278
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