• Laser & Optoelectronics Progress
  • Vol. 57, Issue 15, 153001 (2020)
Qidong Zhao1、2、**, Xiangyu Ge1、2, Jianli Ding1、2、*, Jingzhe Wang1、2、3, Zhenhua Zhang1、2, and Meiling Tian1、2
Author Affiliations
  • 1Key Laboratory of Oasis Ecology, Ministry of Education, Xinjiang University, Urumqi, Xinjiang 830046, China
  • 2Key Laboratory of Smart City and Environmental Modelling of Higher Education Institute, College of Resource and Environmental Sciences, Xinjiang University, Urumqi, Xinjiang 830046, China
  • 3Guangdong Institute of Eco-Environmental Science and Technology, Guangzhou, Guangdong 510650, China
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    DOI: 10.3788/LOP57.153001 Cite this Article Set citation alerts
    Qidong Zhao, Xiangyu Ge, Jianli Ding, Jingzhe Wang, Zhenhua Zhang, Meiling Tian. Combination of Fractional Order Differential and Machine Learning Algorithm for Spectral Estimation of Soil Organic Carbon Content[J]. Laser & Optoelectronics Progress, 2020, 57(15): 153001 Copy Citation Text show less
    SOC content statistics
    Fig. 1. SOC content statistics
    Spectral reflectance curves of soil with different organic carbon content
    Fig. 2. Spectral reflectance curves of soil with different organic carbon content
    Number of bands whose correlation coefficient passes significance test level of 0.01
    Fig. 3. Number of bands whose correlation coefficient passes significance test level of 0.01
    Thermal map of correlation coefficient between SOC content and different orders at each bands
    Fig. 4. Thermal map of correlation coefficient between SOC content and different orders at each bands
    OrderR2RMSERPD
    00.5382.1761.347
    0.20.5602.1611.283
    0.40.6411.9231.516
    0.60.3612.5291.061
    0.80.5812.2291.323
    1.00.2742.8730.917
    1.20.3612.8720.997
    1.40.3452.6671.027
    1.60.2472.8500.961
    1.80.0623.3960.801
    2.00.1962.9760.905
    Table 1. Simulation results of ELM modeling algorithm
    OrderR2RMSEPD
    00.7631.1692.389
    0.20.7801.1322.440
    0.40.7991.0492.640
    0.60.8071.9052.313
    0.80.7991.9972.614
    1.00.8031.1312.274
    1.20.8161.1522.458
    1.40.8261.1302.588
    1.60.8281.0142.858
    1.80.8161.1892.259
    2.00.8211.1422.466
    Table 2. Simulation results of RF modeling algorithm
    OrderR2RMSERPD
    00.6212.0471.470
    0.20.7101.7241.774
    0.40.7951.5221.923
    0.60.7091.7081.670
    0.80.8301.4642.113
    1.00.8291.4712.149
    1.20.8461.2182.604
    1.40.8671.0712.783
    1.60.8451.2312.535
    1.80.8471.1752.656
    2.00.8441.1722.681
    Table 3. Simulation results of MARS modeling algorithm
    OrderR2RMSERPD
    00.5862.0951.325
    0.20.5902.0811.367
    0.40.6261.9771.466
    0.60.7781.5071.989
    0.80.8012.7061.141
    1.00.8371.2042.169
    1.20.8461.1492.207
    1.40.8491.1302.548
    1.60.8691.0352.798
    1.80.8481.1202.663
    2.00.8431.1222.562
    Table 4. Simulation results of Elastic Net modeling algorithm
    OrderR2RMSERPD
    00.7881.9162.162
    0.20.7931.8832.275
    0.40.8141.7122.618
    0.60.8301.5262.707
    0.80.8411.3812.848
    1.00.8461.2762.267
    1.20.8471.2902.679
    1.40.8571.2572.882
    1.60.8781.1253.142
    1.80.8511.2822.798
    2.00.8481.2642.813
    Table 5. Simulation results of GBRT modeling algorithm
    BandVisibleNear infrared
    Wavelength /nm500620890140022002300
    Chemical bondFe—O、C—HC—HO—HAl—OHC—H
    Table 6. Comparison of effects of different bands on molecular chemical bonds in soil
    Qidong Zhao, Xiangyu Ge, Jianli Ding, Jingzhe Wang, Zhenhua Zhang, Meiling Tian. Combination of Fractional Order Differential and Machine Learning Algorithm for Spectral Estimation of Soil Organic Carbon Content[J]. Laser & Optoelectronics Progress, 2020, 57(15): 153001
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