Spectroscopy and Spectral Analysis, Volume. 41, Issue 11, 3424(2021)

Estimation of Organic Matter, Moisture, Total Iron and pH From Back Soil Based on Multi Scales SNV-CWT Transformation

Yang TAN, Qi-gang JIANG*;, Hua-xin LIU, Bin LIU, Xin GAO, and Bo ZHANG
Author Affiliations
  • College of Geo-exploration Science and Technology, Jilin University, Changchun, 130026, China
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    Figures & Tables(10)
    Study area and sampling regions
    Reflectance spectraunder different transformation methods
    Raw reflectance spectra of dry and wet samples
    Coefficients of determination (R2) corresponding to different soil properties on multi SNV-CWT scales
    Correlations between different soil properties and reflectance before and after SNV-CWT
    Statistical indicators of models taking bands selected by MBC as input variables
    • Table 1. Statistical values of soil component from study area

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      Table 1. Statistical values of soil component from study area

      ContentsMaxMinMeanSDCV/%
      SOM/(g·kg-1)63.3619.8734.8612.6536.29
      SMC/(g·kg-1)244.6138.02105.2546.8244.54
      Fe/(g·kg-1)33.6323.0227.162.127.81
      pH8.094.735.740.7713.41
    • Table 2. Statistical indicators ofvalidation models of SOM, SMC, Fe and pHunder different transformation methods

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      Table 2. Statistical indicators ofvalidation models of SOM, SMC, Fe and pHunder different transformation methods

      ContentsSIRawFDSDCRSNVMSCGSLog(1/R)SNV-CWT
      R20.430.830.700.730.840.680.740.430.90
      SOMMse0.830.250.440.400.230.470.380.830.15
      RPD1.462.511.852.012.711.761.971.373.21
      R2-0.830.870.770.790.740.360.020.93
      SMCMse-3.092.324.283.834.8311.7218.681.37
      RPD-2.793.492.452.342.341.261.134.71
      R2--0.200.170.140.090.27-0.48
      FeMse--0.030.030.030.030.03-0.02
      RPD--1.121.101.111.051.18-1.39
      R2-0.440.360.640.610.280.390.130.62
      pHMse-0.270.320.180.190.360.300.880.19
      RPD-1.381.271.671.601.181.280.951.63
    • Table 3. Statistical indicators of models taking bands selected by PCC as input variables

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      Table 3. Statistical indicators of models taking bands selected by PCC as input variables

      ContentsNTMaxMinR2MseRPD
      SOM30.800.8100.910.123.49
      SMC990.750.9000.911.664.22
      Fe750.110.2200.430.021.34
      pH710.290.4400.650.171.73
    • Table 4. Statistical indicators of models taking bands selected by GRA as input variables

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      Table 4. Statistical indicators of models taking bands selected by GRA as input variables

      ContentsNTMaxMinR2MseRPD
      SOM20.900.900.680.910.133.32
      SMC890.920.950.740.901.764.02
      Fe800.810.830.740.450.021.38
      pH980.820.850.700.650.171.75
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    Yang TAN, Qi-gang JIANG, Hua-xin LIU, Bin LIU, Xin GAO, Bo ZHANG. Estimation of Organic Matter, Moisture, Total Iron and pH From Back Soil Based on Multi Scales SNV-CWT Transformation[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3424

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    Paper Information

    Category: Orginal Article

    Received: Jan. 25, 2021

    Accepted: --

    Published Online: Dec. 17, 2021

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2021)11-3424-07

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