Extracting shelter forest in semi-arid sandy area based on Landsat ETM+ imagery

摘要

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.