DocumentCode :
2904384
Title :
Using Multi-spectral Remote Sensing Data to Extract and Analyze the Vegetation Information in Desert Areas
Author :
Zhao, Huai-Bao ; Liu, Tong ; Cui, Yao-Ping ; Lei, Jia-Qiang
Author_Institution :
Xinjiang Inst. of Ecology & Geogr., Chinese Acad. of Sci., Urumqi, China
Volume :
3
fYear :
2009
fDate :
4-5 July 2009
Firstpage :
697
Lastpage :
702
Abstract :
The coverage and spatial distribution of vegetation in desert areas are fundamental indexes to estimate the desertification severity, and acquiring vegetation information is very beneficial to carry out desertification monitoring and evaluation. Based on Landsat TM image of 2007, vegetation information of the western Gurbantunggut Desert was extracted with vegetation indexes and spectral mixture analysis. The results show that: the U-min method (one of the SMA methods) is the best one and this method was used for further analysis. Moreover, a significant linear relationship is found between vegetation coverage and vegetation fraction extracted from SMA, with a correlation coefficient of 0.858. This indicate that vegetation coverage in desert areas can be extracted through remote sensing images indirectly.
Keywords :
feature extraction; remote sensing; vegetation; Gurbantunggut Desert; Landsat TM image; SMA methods; U-min method; desert areas; desertification monitoring; desertification severity; remote sensing; spatial distribution; time 2007 year; vegetation information; Data mining; Environmental factors; Geography; Image analysis; Information analysis; Monitoring; Remote sensing; Satellites; Spectral analysis; Vegetation mapping; Gurbantunggut desert; NDVI; TM image; spectral mixture 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.2009.522
Filename :
5199789
Link To Document :
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