Mountain glacier identification from SAR images

Hong'an Wu; Yonghong Zhang; Weifan Zhong; Guangtong Sun

doi:10.1117/12.901636

23 November 2011 Mountain glacier identification from SAR images

Hong'an Wu, Yonghong Zhang, Weifan Zhong, Guangtong Sun

Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 80060B (2011) https://doi.org/10.1117/12.901636
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Because the terrain of mountain glacier is usually very rugged, it is hard to measure glaciers and estimated their changes in larger area by conventional measuring method. With fast development of remote sensing technique, synthetic aperture radar (SAR) interferometry is used for glacier monitoring with the ability of all-time and all-weather. Although interferometric coherence is a very good index to glacier, it is difficult to distinguish glacier area from non-glacier 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. 8 texture features were analyzed based on co-occurrence matrix (COM), including mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation. Among them, variance, contrast and dissimilarity can distinguish glacier from non-glacier clearly most, so they are chosen for RGB combination. Then the RGB combination image is classified into several land covers by maximum likelihood classification (MLC). With post-classification processing, glacier area can be extracted accurately. Landsat TM images validate the proposed method.

Citation Download Citation

Hong'an Wu, Yonghong Zhang, Weifan Zhong, and Guangtong Sun "Mountain glacier identification from SAR images", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060B (23 November 2011); https://doi.org/10.1117/12.901636

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KEYWORDS

Interferometry

Synthetic aperture radar

Phase interferometry

Earth observing sensors

Remote sensing

Landsat

RGB color model

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