Journal of Geo-information Science, Volume. 22, Issue 2, 308(2020)

Estimation Model of Equivalent Water Thickness in the Road Area

Yunkai GUO1...1,2,2, Xiaojiong ZHANG1,1,2,2,*, Min XU1,1,2,2, Yuling LIU1,1, Jia QIAN1,1, and Qiong ZHANG11 |Show fewer author(s)
Author Affiliations
  • 1School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410014, China
  • 1长沙理工大学交通运输工程学院,长沙 410014
  • 2Institute of Surveying and Mapping Remote Sensing Application Technology, Changsha University of Science & Technology, Changsha 410076, China
  • 2长沙理工大学测绘遥感应用技术研究所,长沙 410076
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    Figures & Tables(6)
    Comparison of estimated EWT by three models
    Fitting relationship between predicted and measured values of EWT
    • Table 1. Input parameters of the PRO4SAIL model

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      Table 1. Input parameters of the PRO4SAIL model

      输入参数输入值
      结构参数(N1.22
      叶绿素含量(Cab)/(μg/cm242.93
      类胡萝卜素含量(Car)/(μg/cm28
      褐色素含量(Cbrown)/(μg/cm20
      干物质重量(Cm)/(μg/cm20.02316
      平均叶倾角(LAD30
      叶面积指数(LAI4~6,步长:0.2
      等效水厚度(EWT0.01~0.03,步长:0.001
      热点参数(hspot0.15
      太阳天顶角(θs)/°23.9
      观测天顶角(θv)/°0
      土壤反射率(rsoil0.2
    • Table 2. Twelve different water indices

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      Table 2. Twelve different water indices

      水分指数计算公式公式编号参考文献
      新近红外肩部区域光谱比值指数(Spectral Ratio Index in theNIR Shoulder Region, NSRI)NSRI=ρ890ρ780(1)[15]
      水分指数(Water Index, WI)WI=ρ900ρ970(2)[15]
      归一化差值植被指数(Normalized difference vegetation index, NDVI)NDVI=(ρ860-ρ680)(ρ860+ρ680)(3)[15]
      归一化差值红外指数 (Normalized Difference Infrared Index, NDII)NDII=(ρ850-ρ1650)(ρ850+ρ1650)(4)[15]
      Datt水分指数(DattWater Index, DWI)DWI=(ρ816-ρ2218)(ρ816+ρ2218)(5)[15]
      简单水比指数(Simple Ratio Water Index, SRWI)SRWI=ρ860ρ1240(6)[15]、[20]
      湿度胁迫指数(Moisture Stress Index, MSI)MSI=ρ1600ρ819(7)[15]、[19]
      水比指数(Simple Ratio, SR)SR=ρ895ρ675(8)[15]
      归一化差值水分指数(Normalized Difference Water Index, NDWI)NDWI=(ρ860-ρ1240)(ρ860+ρ1240)(9)[15]
      归一化多波段干旱指数(NormalizedMulti-band Drought Index, NMDI)NMDI=ρ860-(ρ1640-ρ2130)ρ860+(ρ1640+ρ2130)(10)[15]
      全球植被水分指数(Global Vegetation Moisture Index, GVWI)GVWI=(ρ820+0.1)-(ρ1600-0.02)(ρ820+0.1)+(ρ1600+0.02)(11)[18]
      土壤调整植被指数(Soil Adjusted Vegetation Index, SAVI)SAVI=ρ860-ρ680×(1+L)(ρ860+ρ860+L),L=0.5(12)[18]
    • Table 3. Importance analysis and ordination between the water indices and EWT

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      Table 3. Importance analysis and ordination between the water indices and EWT

      特征编号植被指数重要性特征编号植被指数重要性
      1NDWI0.22417DWI0.0678
      2NMDI0.19328MSI0.0571
      3SRWI0.15819SAVI0.0491
      4SR0.073410NSRI0.0301
      5NDII0.072311NDVI0.0033
      6WI0.071112GVWI0.0003
    • Table 4. Descriptive statistics of the data samples for modeling and validation

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      Table 4. Descriptive statistics of the data samples for modeling and validation

      反演模型建模样本预测样本
      自变量应变量自变量应变量
      PLSPRO4SAIL模拟NDWINMDISRWISRPRO4SAIL模拟EWT实测NDWINMDISRWISR实测EWT
      SVMPRO4SAIL模拟NDWINMDISRWISRNDIIWIDWIMSISAVIPRO4SAIL模拟EWT实测NDWINMDISRWISRNDIIWIDWIMSISAVI实测EWT
      GA-SVMPRO4SAIL模拟NDWINMDISRWISRPRO4SAIL模拟EWT实测NDWINMDISRWISR实测EWT
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    Yunkai GUO, Xiaojiong ZHANG, Min XU, Yuling LIU, Jia QIAN, Qiong ZHANG. Estimation Model of Equivalent Water Thickness in the Road Area[J]. Journal of Geo-information Science, 2020, 22(2): 308

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    Paper Information

    Received: May. 22, 2019

    Accepted: --

    Published Online: Sep. 16, 2020

    The Author Email: ZHANG Xiaojiong (1183582609@qq.com)

    DOI:10.12082/dqxxkx.2020.190254

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