Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Acta Optica Sinica, Volume. 42, Issue 22, 2230002(2022)

Inversion of Soil Iron Oxide Based on Multi-Scale Continuous Wavelet Decomposition

Hailong Zhao1, Shu Gan1,2、*, Xiping Yuan2,3, Lin Hu1, Shuai Liu1, and Junjie Wang1
Author Affiliations
  • 1Faculty of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan , China
  • 2Yunnan Institute of Engineering Research and Application of Plateau Mountain Spatial Information Surveying and Mapping Technology, Kunming 650093, Yunnan , China
  • 3West Yunnan University of Applied Sciences, Dali671000, Yunnan , China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (9)
    Equations (0)
    References (23)
    Cited By (2)
    Tools
    Paper Information
    Topics
    Figures & Tables(9)
    Distribution map of soil sampling points

    Fig. 1. Distribution map of soil sampling points

    Download full size
    Original spectral reflectance curves of all soil samples

    Fig. 2. Original spectral reflectance curves of all soil samples

    Download full size
    Correlation coefficient between spectrum and iron oxide content

    Fig. 3. Correlation coefficient between spectrum and iron oxide content

    Download full size
    Thermodynamic diagram of wavelet coefficient and coefficient of determination of iron oxide content

    Fig. 4. Thermodynamic diagram of wavelet coefficient and coefficient of determination of iron oxide content

    Download full size
    Characteristic wavelengths selected by CC-CARS algorithm

    Fig. 5. Characteristic wavelengths selected by CC-CARS algorithm

    Download full size
    Scatter plot of measured and predicted values of soil iron oxide content under different models. (a) L4-CC-CARS-SVR; (b) OS-CC-CARS-SVR; (c) FD-CC-CARS-SVR; (d) RL-CC-CARS-SVR

    Fig. 6. Scatter plot of measured and predicted values of soil iron oxide content under different models. (a) L4-CC-CARS-SVR; (b) OS-CC-CARS-SVR; (c) FD-CC-CARS-SVR; (d) RL-CC-CARS-SVR

    Download full size

    • Table 1. Statistical characteristics of iron oxide content

      View table

      Table 1. Statistical characteristics of iron oxide content

      Sample classificationSample number

      Maximum /

      （g·kg-1）

      Minimum /

      （g·kg-1）

      Mean /

      （g·kg-1）

      Standard deviation /

      （g·kg-1）

      		Variable coefficient /%
      Total set13566.97818.29341.20111.69828.393
      Calibration set9564.80823.31142.14110.73625.476
      Validation set4066.97818.29338.96913.60534.912
      Red soil6866.97823.29746.83811.80425.016
      Purple soil4862.36523.31135.8347.84021.880
      Yellow brown soil1954.35618.29334.5839.55928.400

    • Table 2. Correlation analysis of transform spectrum and iron oxide content

      View table

      Table 2. Correlation analysis of transform spectrum and iron oxide content

      Transform spectrumWavelet decomposition scaleSignificant band numberMaximum correlation coefficient
      CWTL192-0.590
      L2171-0.593
      L33950.606
      L4663-0.602
      L511360.603
      L61056-0.604
      L713200.527
      L81357-0.511
      L91273-0.548
      L101447-0.523
      OS2051-0.589
      FD1252-0.548
      RL20510.606

    • Table 3. Results of soil iron oxide inversion model

      View table

      Table 3. Results of soil iron oxide inversion model

      Transform spectrumCalibration setValidation set
      R2ERMSE /（g·kg-1）R2ERMSE /（g·kg-1）RPIQ
      L10.7834.9690.16812.2511.654
      L20.6915.9320.37010.6571.901
      L30.8254.4640.5908.6002.356
      L40.7605.2360.6637.7982.598
      L50.6226.5650.6378.0952.503
      L60.5487.1830.4509.9672.034
      L70.7695.1330.6188.2982.442
      L80.5117.4630.4989.5172.129
      L90.3218.8010.10212.7261.592
      L100.3409.5930.34211.5481.755
      OS0.6786.0620.6168.3282.433
      FD0.6476.3430.6388.0762.509
      RL0.7445.4020.6378.0922.504
    Tools

    Get Citation

    Copy Citation Text

    Hailong Zhao, Shu Gan, Xiping Yuan, Lin Hu, Shuai Liu, Junjie Wang. Inversion of Soil Iron Oxide Based on Multi-Scale Continuous Wavelet Decomposition[J]. Acta Optica Sinica, 2022, 42(22): 2230002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: Spectroscopy

    Received: Apr. 8, 2022

    Accepted: May. 27, 2022

    Published Online: Nov. 7, 2022

    The Author Email: Gan Shu (1193887560@qq.com)

    DOI:10.3788/AOS202242.2230002

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology