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Proceedings Paper

Extracting shelter forest in semi-arid sandy area based on Landsat ETM+ imagery
Author(s): Xin Qi; Fang Huang; Yina Qi
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Paper Abstract

Taking a sub-area of semi-arid west Jilin Province as example, we mainly discuss the method of shelter forest extraction in sandy area from Landsat-7 ETM+ imagery in this study. After the comparison of the image fusion methods including HIS transforms, PCA transforms, Brovey transforms and Wavelet transforms, the method of Brovey transforms improved by wavelet analysis is presented for further processing. The details information in fused ETM+ image by this improved method is more considerable and fruitful. Using unsupervised classification in combination with supervised classification and threshold method based on NDVI, we extract the farmland shelterbelts from the fusion image finally. The accuracy of classification is more than 85%. From the experiment result, this method shows a better performance in the shelter forest extraction in a typical semi-arid sandy.

Paper Details

Date Published: 7 November 2008
PDF: 10 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470Q (7 November 2008); doi: 10.1117/12.813227
Show Author Affiliations
Xin Qi, Northeast Normal Univ. (China)
Fang Huang, Northeast Normal Univ. (China)
Yina Qi, Northeast Normal Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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