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Wu, H.; Zhang, Y.; Zhang, J.; Lu, Z.; Zhong, W. (2012)
Publisher: Copernicus Publications
Languages: English
Types: Article
Subjects: TA1-2040, T, TA1501-1820, Applied optics. Photonics, Engineering (General). Civil engineering (General), Technology
Accurate monitoring of the glacier changes is essential to evaluate the environmental-ecological health in the scenario of global change. Conventional method for glacial monitoring is optical remote sensing. However, affected by cloud and snow cover, it is hard to monitor glacier by optical images. With the fast development of InSAR technique, interferometric coherence has been utilized for extracting glacial information. However, it is difficult to distinguish glacial area from non-glacial area when their coherence is similar, especially for short wavelength radar, such as X-band and C-band. 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 gray level co-occurrence matrix (GLCM), 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). After post-classification processing, glacial area can be extracted accurately. With this proposed method, two ERS-2 SAR single look complex (SLC) images acquired in 1997 and two ENVISAT ASAR SLC images acquired in 2007 are used to extract glacial area in 1997 and 2007 over Geladandong area, the head of the Yangtze River. The extracted areas are validated by Landsat TM data, which indicate that the proposed method can obtain accurate glacial area. The results also demonstrate during the 10 years, glacial area over Geladandong decreased fast, with a reduction of 22.97km2.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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