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
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