Title
An Index of Vegetation Water Content Invasion by Landsat 5, in Semi-arid Area: The Tarim River Basin
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 EWT sparsecanopy from the Landsat TM imagery.
Year
DOI
Venue
2009
10.1109/ESIAT.2009.519
ESIAT (2)
Keywords
Field
DocType
vegetation water content invasion,vegetation water content,semiarid area,equivalent water thickness,spectral index,tarim river basin,quantitatively retrieving vegetation water,vegetation water content effect,water cycle process,semi-arid area,index ewtsparsecanopy,infrared index,ewt sparsecanopy,reflectivity,regression equation,vegetation,earth,feature extraction,remote sensing,china,signal processing,satellites,moisture,indexes,regression analysis,water cycle,indexation,river basin,infrared
Moisture,Vegetation,Satellite,Arid,Drainage basin,Computer science,Hydrology,Vegetation water content,Enhanced vegetation index,Water cycle
Conference
Citations 
PageRank 
References 
0
0.34
1
Authors
5
Name
Order
Citations
PageRank
Chang Cun101.01
Chen Xi214.11
Anming Bao3168.39
Ma Zhongguo400.34
Wang Jinlin500.68