Journal of Infrared and Millimeter Waves, Volume. 43, Issue 2, 226(2024)

Difference and parameter analysis of LST inversion based on Landsat data

Ji-Kang WAN1、*, Zhe-Hui SHEN2, and Shan LI3
Author Affiliations
  • 1School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,China
  • 2College of Civil Engineering,Nanjing Forestry University,Nanjing 210037,China
  • 3School of Economics and Management,Fuzhou University,Fuzhou 350108,China
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    Figures & Tables(13)
    Study areas,(a) the remote sensing data of ‘LC08_L1TP_123032_20211126_20211201_02_T1’;(b) the remote sensing data of ‘LC09_L1TP_123032_20211122_20220120_02_T1’,with green dots representing the location of the meteorological station
    Overall research process,ε represents land surface emissivity,w represents water vapor content,(g·cm-2),L↓ represents downwelling radiance,(W/m2/sr/um),L↑ represents upwelling radiance,(W/m2/sr/um),τ represents atmospheric transmittance
    Inversion results of 5 LST inversion algorithms
    The inversion results of the algorithm fit the measured values
    Parameter sensitivity analysis
    Stability statistics of five inversion algorithms on different land covers
    • Table 1. Different LST inversion methods

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      Table 1. Different LST inversion methods

      ModelModel + parameterModel ID
      RTERTE (LSE,τL, LLST1
      SCSC (wLST2
      SC (LSE,τL, LLST3
      SWSW (by Jiménez-Muñoz et al.) (LSE, wLST4
      MWMW (LSE,τL, L ,Ta)LST5
    • Table 2. The selection length and step size of each parameter

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      Table 2. The selection length and step size of each parameter

      ParameterLengthStep size
      LSE(0.9,1.0)0.01
      τ(0.5,1.0)0.01
      L(0,5)0.1
      L(0,5)0.1
      w(0,2.5)0.1
    • Table 3. LST1 statistical results

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      Table 3. LST1 statistical results

      Land CoverLandsat-8 (° CLandsat-9 (° C
      MaxMinMeanStdMaxMinMeanStd
      Water6.2340.7842.7830.5761.872-4.324-2.7620.425
      Vegetation6.9824.8245.2340.8232.731-2.9730.8320.756
      Dark buildings24.832-7.9835.7593.32021.870-9.8324.8623.013
      Bright soil12.0735-8.0896.2314.43211.872-6.2733.2814.171
      Dark soil10.380-7.7830.1941.4719.384-5.923-0.8271.362
      High reflectivity buildings22.447-7.3684.2805.3918.319-9.8733.9764.792
    • Table 4. LST2 statistical results

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      Table 4. LST2 statistical results

      Land CoverLandsat-8 (° CLandsat-9 (° C
      MaxMinMeanStdMaxMinMeanStd
      Water13.3453.5637.4532.5447.456-5.6492.4792.325
      Vegetation14.6825.5748.0162.69011.932-3.9732.8322.456
      Dark buildings25.341-5.3989.7594.32018.840-8.4526.8624.013
      Bright soil23.735-4.8098.2564.47215.872-4.7435.8134.311
      Dark soil22.120-6.4533.9443.71618.854-4.9311.6733.326
      High reflectivity buildings26.423-4.3187.2085.32121.394-11.3541.9764.942
    • Table 5. LST3 statistical results

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      Table 5. LST3 statistical results

      Land CoverLandsat-8 (° CLandsat-9 (° C
      MaxMinMeanStdMaxMinMeanStd
      Water5.9330.8822.8810.4741.832-4.324-2.4530.318
      Vegetation6.7454.4565.6750.8572.456-2.6750.8480.796
      Dark buildings23.124-7.8755.2343.35221.345-9.3734.3673.274
      Bright soil21.923-8.3556.3334.24519.123-6.1713.1614.081
      Dark soil21.485-7.2451.2451.57117.345-5.235-0.1451.461
      High reflectivity buildings23.232-7.5675.8465.47822.487-10.4843.3534.863
    • Table 6. LST4 statistical results

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      Table 6. LST4 statistical results

      Land CoverLandsat-8 (° CLandsat-9 (° C
      MaxMinMeanStdMaxMinMeanStd
      Water14.2343.1236.6530.9777.852-5.321-1.1220.855
      Vegetation15.9487.8249.2340.9998.731-1.9732.8320.966
      Dark buildings28.852-6.7636.2394.32820.874-8.8356.8624.513
      Bright soil27.075-8.2198.2224.93215.842-9.2135.2814.672
      Dark soil27.122-6.2135.2343.34618.314-8.123-4.2373.862
      High reflectivity buildings27.227-8.2348.1235.72120.391-13.3432.3425.212
    • Table 7. LST5 statistical results

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      Table 7. LST5 statistical results

      Land CoverLandsat-8 (° CLandsat-9 (° C
      MaxMinMeanStdMaxMinMeanStd
      Water14.4743.28425.7341.5263.872-6.343-3.7221.352
      Vegetation13.9227.8218.9341.9826.721-5.9233.8231.846
      Dark buildings27.456-9.3458.2343.88720.238-8.7942.5643.713
      Bright soil26.035-7.3495.3574.63120.412-7.4567.5674.671
      Dark soil27.546-8.3454.6343.57516.435-6.456-3.6243.387
      High reflectivity buildings28.673-5.3456.2345.59320.334-9.8344.9744.891
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    Ji-Kang WAN, Zhe-Hui SHEN, Shan LI. Difference and parameter analysis of LST inversion based on Landsat data[J]. Journal of Infrared and Millimeter Waves, 2024, 43(2): 226

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    Paper Information

    Category: Research Articles

    Received: Jun. 28, 2023

    Accepted: --

    Published Online: Apr. 29, 2024

    The Author Email: Ji-Kang WAN (jackvanvip@163.com)

    DOI:10.11972/j.issn.1001-9014.2024.02.012

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