• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 8, 2572 (2022)
Ge WANG1,*, Qiang YU1,1; *;, Di Yang2,2;, Teng NIU1,1;..., Qian-qian LONG1,1; and 2,2;|Show fewer author(s)
Author Affiliations
  • 11. Beijing Key Laboratory of Precision Forestry, Beijing Forestry University, Beijing 100083, China
  • 22. Geographic Information Center, University of Wyoming, Laramie 82070, USA
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    DOI: 10.3964/j.issn.1000-0593(2022)08-2572-07 Cite this Article
    Ge WANG, Qiang YU, Di Yang, Teng NIU, Qian-qian LONG, [in Chinese]. Retrieval of Dust Retention Distribution in Beijing Urban Green Space Based on Spectral Characteristics[J]. Spectroscopy and Spectral Analysis, 2022, 42(8): 2572 Copy Citation Text show less
    Distribution of sampling points
    Fig. 1. Distribution of sampling points
    Indoor dust retention capacity and spectral determination process of leaves (a) and principle of spectral determination of leaves (b)
    Fig. 2. Indoor dust retention capacity and spectral determination process of leaves (a) and principle of spectral determination of leaves (b)
    Land covers and urban green spaces of beijing in 2020
    Fig. 3. Land covers and urban green spaces of beijing in 2020
    Effect of dust retention on spectral characteristics (a) and spectral curve (b) after first derivative over treatment before and after dust removal
    Fig. 4. Effect of dust retention on spectral characteristics (a) and spectral curve (b) after first derivative over treatment before and after dust removal
    Relationship between dust retention and spectral reflectance ratio (before and after dust removal)
    Fig. 5. Relationship between dust retention and spectral reflectance ratio (before and after dust removal)
    Inversion model based on EVI index
    Fig. 6. Inversion model based on EVI index
    Dust retention distribution of green space in Beijing (a) and dust retention inversion verification (b)
    Fig. 7. Dust retention distribution of green space in Beijing (a) and dust retention inversion verification (b)
    Distribution of atmospheric dust pollution in Beijing and spatial autocorrelation analysis
    Fig. 8. Distribution of atmospheric dust pollution in Beijing and spatial autocorrelation analysis
    植被指数计算公式植被指数比
    (滞尘/除尘)
    NDVINDVI=NIR-RNIR+RRNDVI=NDVIdustNDVIclean
    RVIRVI=NIRRRRVI=RVIdustRVIclean
    DVIDVI=NIR-RRDVI=DVIdustDVIclean
    PVIPVI=NIR-10.489R-6.6604)(1+10.4892(10.547)RPVI=PVIdustPVIclean
    EVIEVI=2.5(NIR-R)NIR+6R-7.5B+1REVI=EVIdustEVIclean
    GNDVIGNDVI=NIR-GNIR+GRGNDVI=GNDVIdustGNDVIclean
    RDVIRDVI=NIR-RNIR+RRRDVI=RDVIdustRDVIclean
    SAVISAVI=NIR-RNIR+R+L(1+L),
    L=0.5
    RSAVI=SAVIdustSAVIclean
    OSAVIOSAVI=NIR-RNIR+R+0.16ROSAVI=OSAVIdustOSAVIclean
    NLINLI=(NIR)2-R(NIR)2+RRNLI=NLIdustNLIclean
    Table 1. vegetation index formula
    参数类型含义除尘前除尘后
    蓝边幅值红边(490~530 nm)内一阶导数最大值0.0020.003
    黄边幅值黄边(560~640 nm)内一阶导数最大值-0.001-0.002
    红边幅值红边(680~760 nm)内一阶导数最大值0.0120.016
    蓝边面积蓝边内一阶微分的总和6.7257.704
    黄边面积黄边内一阶微分的总和14.90415.278
    红边面积红边内一阶微分的总和37.03943.282
    Table 2. Effect of dust retention on blue, yellow and red edges of spectrum
    Sentinel-2Landsat8MODISZY3Spot6
    NDVI-0.412-0.375-0.362-0.339-0.372
    RVI-0.398-0.348-0.341-0.331-0.328
    DVI-0.768**-0.689-0.679-0.681-0.683
    PVI0.4010.4490.4730.4510.475
    EVI-0.809**-0.745**-0.719**-0.718**-0.748**
    GNDVI-0.379-0.288-0.268-0.288-0.292
    RDVI-0.351-0.521-0.273-0.502-0.508
    SAVI-0.512-0.522-0.518-0.481-0.471
    OSAVI-0.458-0.401-0.405-0.395-0.389
    NLI-0.561-0.409-0.507-0.498-0.495
    Table 3. Relationship between vegetation index ratio and dust retention of five satellites
    模型类型反演模型R2RMSE
    线性y=-22.74x+25.740.7051.691
    二次y=49.52x2-102.3x+57.10.7511.298
    Table 4. Dust retention inversion model
    Ge WANG, Qiang YU, Di Yang, Teng NIU, Qian-qian LONG, [in Chinese]. Retrieval of Dust Retention Distribution in Beijing Urban Green Space Based on Spectral Characteristics[J]. Spectroscopy and Spectral Analysis, 2022, 42(8): 2572
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