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A New Method for Extracting Glacier Area Using SAR Interferometry

Image and Data Fusion(2011)

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摘要
Although interferometric coherence is a very good index to glacier, it is difficult to distinguish glacial area from non-glacial area when their coherence is similar. In this case, interferometric phase can play an important role to identify glacier. In this paper, phase texture analysis method is proposed to extract glacier based on gray level co-occurrence matrix (GLCM). Among eight texture features, variance, contrast and dissimilarity can distinguish glacier from non-glacier clearly best, so they are chosen for RGB combination. Then the RGB combination image is used to extract glacier by maximum likelihood classification (MLC). The result is validated by Landsat TM data, which demonstrate that the proposed method can obtain accurate glacial area.
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关键词
synthetic aperture radar,glaciology,phase texture analysis,maximum likelihood estimation,china,hydrological techniques,remote sensing by radar,rgb combination image,feature extraction,image classification,interferometric coherence,geophysical image processing,glacier,image texture features,gray level co-occurrence matrix,maximum likelihood classification,geladandong,radar interferometry,sar interferometry,image texture,glacier area data extraction,landsat tm data,gray level co-occurrence matrix (glcm),interferometric phase,optical interferometry,indexation,earth,coherence,satellites,remote sensing
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