(c) (d) 
Figure 5. Extracted glacial area from 2 ERS ASAR images 
acquired in 1997 over Geladandong region: (a) RGB pseudo- 
color combination of variance, contrast and dissimilarity; (b) 
MLC result; (c) glacial area after post classification process; (d) 
geo-coded glacial area 
  
(a) (b) 
Figure 6. Extracted glacial area from 2 ENVISAT ASAR 
images acquired in 2007: (a) interferometric phase; (b) geo- 
coded glacier area 
5. VALIDATION 
In this research, optical satellite image (Landsat TM) is used to 
validate the result extracted from SAR data. Due to the lack of 
TM images over Geladandong in summer of 1997, TM image 
obtained on May 5 2007 is selected to validate the extracted 
glacial area from ENVISAT ASAR images. Figure7 (a) shows 
TM pseudo-colour image by the combination of band 543. 
Figure7 (b) is extracted result using MLC and the glacial area is 
825.61 km’. The relative difference of glacial area extracted 
from ASAR and TM is 1.66%. This indicates that the proposed 
method based GLCM of interferometric phase for extracting 
glacial area is effective. By analysing the shape of glacial 
coverage, it is clearly seen that SAR layover was the main 
reason for SAR's overestimate, which are shown in Figure 6(b) 
and Figure 7(b) with red circles. 
6. CONCLUSION 
Due to the impact of clouds and snow, optical remote sensing 
images can not effectively monitor the change of glacial areas. 
SAR data has great potential in glacier monitoring by 
interferometry. When the coherence contrast between glacial 
region and non-glacial region is strong, InSAR coherence 
threshold method can extract glacial area accurately. However, 
when this contrast is not obvious, we need a new approach. In 
this paper, interferometric phase analysis based on GLCM is 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
    
proposed to extract glacial area. The result is validated by 
Landsat TM image, which demonstrates that the proposed 
method can achieve accurate glacial area. 
The proposed method is applied to monitor the glacial change 
over Geladandong area, the head of the Yangtze River from 
1997 to 2007, with two ERS-2 SAR SLC imagesand two 
ENVISAT ASAR SLC images. The results demonstrate during 
the 10 years, glacial area over Geladandong decreased fast, with 
a reduction of 22.97km/. 
  
(a) (b) 
Figure 7. Extracted glacial area by Landsat TM data: (a) 
Landsat5 TM image acquired on May 5 2007 (band 543); (b) 
glacial area extracted from TM image 
REFERENCES 
Dwyer, J. L., 1995. Mapping tide-water glacier dynamics in east 
Greenland using Landsat data. Journal of Glaciology, 41(139), 
pp. 584-595. 
Haeberli, W., Cihlar, J., Barry, R G., 2000. Glacier monitoring 
within the Global Climate Observing System. Annals of 
Glaciology, 34, pp. 241-246. 
Haralick, R.M., K. Shanmugan, and I. Dinstein., 1973. Textural 
Features for Image Classification. [EEE Transaction on Systems 
Man, Cybernetics, 3(6), pp. 610-621 
IPCC., 2001. Houghton J T, Ding Y, Griggs D J, et al. Climate 
Change 2001: The Scientific Basis. Contribution of Working 
Group I to the Third Assessment Report. Cambridge Univ. Press, 
Cambridge, UK. 
Kargel, J.S., Abrams, M. J., Bishop, M. P., and et al., 2005. 
Multispectral Imaging contributions to Global Land Ice 
Measurements from Space. Remote Sensing. Environ, 99, pp. 
187-219. 
Li, Z., H. Guo, and X. Li., 2001. SAR Interferometry coherence 
analysis for snow mapping. in Proc. Inter. Geoscience and 
Remote Sensing Symposium, V1, pp. 2905-2907. 
Li Z., Zhou, ‘J,’ Tian, B, Xie, C. 2008. The Glacier 
Identification Using SAR Interfermetric and Polarimetric 
Information in Qinghai-Tibetan Plateau. in Proc. Inter. 
Geoscience and Remote Sensing Symposium, IV, pp.1504-1506 
Li, Z, Sun, W., Zeng, Q. Z., 1998. Measurements of Glacier 
Variation in the Tibetan Plateau Using Landsat Data. Remote 
Sensing of Environment, 63(3), pp. 258-264.