• DocumentCode
    496986
  • Title

    An Index of Vegetation Water Content Invasion by Landsat 5, in Semi-arid Area: The Tarim River Basin

  • Author

    Cun, Chang ; Xi, Chen ; Anming, Bao ; Zhongguo, Ma ; Jinlin, Wang

  • Author_Institution
    Grad. Univ., Chinese Acad. of Sci., Beijing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    4-5 July 2009
  • Firstpage
    438
  • Lastpage
    442
  • Abstract
    Estimation of vegetation water content is central to the understanding of water cycle processes. The information of vegetation water content presents the healthy condition of the plant. Various methods were used to extract vegetation water content in semiarid area, however, Spectral indices were still widely used. In this paper, a global sensitivity analysis (GSA) using PROSPECT model was used to understand and quantify vegetation water content effects on the signal measured at leaf level. The NIR region was therefore required in combination with SWIR to retrieve equivalent water thickness (EWT). An index EWTsparsecanopy was created to provide an operational method for quantitatively retrieving vegetation water content at satellite scale in a rapid and reliable fashion for sparsely vegetated arid area based in tarim river basin. Compared with EWTcanopy, the former one had a better relationship to normalized difference infrared index(NDII), With the R2 =0.553. Finally, the regression equation(Y=0.05552 +0.53512*NDII) was used to estimate EWTsparsecanopy from the Landsat TM imagery.
  • Keywords
    feature extraction; moisture; regression analysis; rivers; signal processing; vegetation; vegetation mapping; China; Landsat 5 TM imagery; NIR region; PROSPECT model; SWIR; Tarim River Basin; equivalent water thickness; global sensitivity analysis; leaf level; normalized difference infrared index; plant condition; regression equation; semiarid area; signal measurement; sparsely vegetated arid area; spectral index; vegetation water content extraction; water cycle processes; Content based retrieval; Data mining; Environmental factors; Information retrieval; Remote sensing; Rivers; Satellites; Sensitivity analysis; Soil moisture; Vegetation mapping; EWT; NDII; global sensitivity analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environmental Science and Information Application Technology, 2009. ESIAT 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3682-8
  • Type

    conf

  • DOI
    10.1109/ESIAT.2009.519
  • Filename
    5199926