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Remote Sensing Technology and Application  2007, Vol. 22 Issue (5): 581-585    DOI: 10.11873/j.issn.1004-0323.2007.5.581
    
Comparisions of Estimating Methods of Vegetation Fraction Based on “BJ-1” Microsatellite Imagery
LIU Ya-lan1, REN Yu-huan1,CHEN Tao2,ZHANG Long-qi1
1.Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China; 
2.State Key Lab.of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079,China
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Abstract  

BJ-1 Microsatellite is the advanced member of the Disaster Monitoring Constellation (DMC) with two powerful cameras.One camera can monitor coverage of 600km by 600km , while the other developed by Sira, can capture images of a 24km wide strip of ground with a resolution of four metres.Vegetation fraction coverage is an important parameter for describing vegetation quality and indicating ecosystem change.Inthis study, BJ-1 images were used to detect and analyze the vegetation fractional coverage in the basin of Miyunreservoir.Based on the analysis of the current methods, this paper uses three kinds of methods, including Dimidiate PixelModel from Normalized Difference Vegetation Index (NDVI),3-bands Grads Difference Method and a new method based on Renormalized Difference Vegetation index (RDVI).According to the experimentation, the estimating values by RDVI method has abetter relationship with the verification values, while the other two methods appeared a bigger difference with the groundtrue values.On the whole, RDVI method shows good characteristics and can be used in estimating of vegetation fraction in conjunction with BJ-1 satellite image data.

Key words:  BJ-1      Vegetation fraction      NDVI      3-bands grads difference method      RDVI      Basin of Miyun Reservior     
Received:  28 February 2007      Published:  03 September 2010
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LIU Ya-Lan
REN Yu-Huan
CHEN Tao
ZHANG Long-Ji

Cite this article: 

LIU Ya-Lan, REN Yu-Huan, CHEN Tao, ZHANG Long-Ji. Comparisions of Estimating Methods of Vegetation Fraction Based on “BJ-1” Microsatellite Imagery. Remote Sensing Technology and Application, 2007, 22(5): 581-585.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2007.5.581     OR     http://www.rsta.ac.cn/EN/Y2007/V22/I5/581

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