Mountain glacier identification from SAR images
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 cooccurrence 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.
SAR interferometry glacier phase texture analysis co-occurrence matrix
Hong’an Wu Yonghong Zhang Weifan Zhong Guangtong Sun
Key Laboratory of Mapping from Space of State Bureau of Surveying and Mapping, ChineseAcademy of Sur Key Laboratory of Mapping from Space of State Bureau of Surveying and Mapping, Chinese Academy of Su
国际会议
桂林
英文
1-6
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）