Remote Sensing Technology and Application, Volume. 39, Issue 1, 98(2024)

Retrieving CODMn Concentration in Karst Plateau Deep Lake Reservoir Using Sentinel-2 Data

Jiao WANG*, Wei LI, Weiquan ZHAO, Zulun ZHAO, Liang HUANG, and Jiafang YANG
Author Affiliations
  • Institute of Mountain Resources,Guiyang 550001,China
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    Figures & Tables(11)
    Spatial distribution of study area and in-situ sites in “Liang Hu”
    Remote sensing reflectance of MSI bands corresponding to CODMn in-situ locations
    Flowchart for CODMn concentration estimation of Karst Plateau Deep Lake Reservoir using Machine Learning methods
    Comparison of "Two Lakes" based on Sentinel-2 data's prediction results and actual measured values (training set)
    Comparison of "Two Lakes" based on Sentinel-2 data's prediction results and actual measured values (test set)
    "Two lakes" CODMn spatiotemporal distribution
    • Table 1. The major specifications of Sentinel-2 MSI

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      Table 1. The major specifications of Sentinel-2 MSI

      波段分辨率Sentinel-2A/nmSentinel-2B/nm意义
      /m中心波长带宽中心波长带宽
      B160443.927442.345监测近岸水体/大气气溶胶
      B210496.698492.198蓝、绿、红可见光波段
      B310560.04555946
      B410664.53866539
      B520703.919703.820红边监测植被健康信息
      B620740.218739.118
      B720782.528779.728
      B810835.1145833133近红外波段(宽)
      B8a20864.83386432近红外波段(窄)
      B960945.026943.227水蒸气波段
      B10601 373.5751 376. 976卷云波段(短波红外)
      B11201 613.71431 610.4141短波红外波段
      B12202 202.42422 185.7238
    • Table 2. Sentinel-2 (A and B) image references and sample dates

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      Table 2. Sentinel-2 (A and B) image references and sample dates

      采样日期成像日期Sentinel-2 (A/B)(.SAFE)
      2018/4/122018/4/9S2A_MSIL1C_20180409T032541_N0206_R018_T48RXQ_20180409T070457
      2018/10/282018/10/31S2A_MSIL1C_20191031T032851_N0208_R018_T48RXQ_20191031T062949
      2019/4/102019/4/9S2B_MSIL1C_20190409T032539_N0207_R018_T48RXQ_20190409T075904
      2019/8/122019/8/17S2B_MSIL1C_20190817T032539_N0208_R018_T48RXQ_20190817T081113
      2019/10/312019/10/31S2A_MSIL1C_20191031T032851_N0208_R018_T48RXQ_20191031T062949
      2020/4/252020/4/28S2A_MSIL1C_20200428T032541_N0209_R018_T48RXQ_20200428T062927
      2020/8/202020/8/26S2A_MSIL1C_20200826T032541_N0209_R018_T48RXQ_20200826T062908
      2020/11/52020/11/14S2A_MSIL1C_20201114T033011_N0209_R018_T48RXQ_20201114T062024
    • Table 3. Hyper parameters setting and results of cross-validation with Grid-Search

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      Table 3. Hyper parameters setting and results of cross-validation with Grid-Search

      方法超参数Grid-Search值CODMn最终模型参数
      RFRn estimators10、20、50、100、20050
      min_samples_leaf1、5、10、151
      min_samples_split2、5、10、15、2510
      max_depth2、3、4、5、6、7、NoneNone
      SVRC1、2、5、10、25、50、120、256256
      gamma24* np.logspace(-6, 6, num=12)0.007 5
      GPRn-restarts-optimizer4、8、10、12、16、20、32、6410
    • Table 4. Pearson correlation coefficients between MSI bands and in-situ CODMn

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      Table 4. Pearson correlation coefficients between MSI bands and in-situ CODMn

      波段B1B2B3B4B5B6B7B8A
      相关系数0.580.580.700.540.570.490.490.50
    • Table 5. Training set and validation set inversion results

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      Table 5. Training set and validation set inversion results

      波段模型训练集(49个)验证集(21个)
      R2RMSE(mg/L)

      MAPE

      /%

      R2RMSE(mg/L)

      MAPE

      /%

      bandSVR0.610.3912.670.570.379.36
      RFR0.930.175.640.840.225.84
      GPR0.570.4113.810.500.3910.24
      logbandSVR0.670.3611.400.690.318.57
      RFR0.930.175.830.800.256.57
      GPR0.590.4013.290.560.3710.21
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    Jiao WANG, Wei LI, Weiquan ZHAO, Zulun ZHAO, Liang HUANG, Jiafang YANG. Retrieving CODMn Concentration in Karst Plateau Deep Lake Reservoir Using Sentinel-2 Data[J]. Remote Sensing Technology and Application, 2024, 39(1): 98

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    Paper Information

    Category: Research Articles

    Received: Jun. 22, 2022

    Accepted: --

    Published Online: Jul. 22, 2024

    The Author Email: WANG Jiao (wj410804806@gmail.com)

    DOI:10.11873/j.issn.1004-0323.2024.1.0098

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