ABSTRACT
The proposed facies classification approach uses three features of the GLCM with multitemporal X-band SAR data of TerraSAR-X combined with k-means clustering. This approach was tested on 15 transboundary Himalayan glaciers. They were classified into six facies namely debris, dry snow, wet snow, bare ice, percolation zone 1 and percolation zone 2 and the covered areas for these classes are 20.56%, 12.50%, 20.26%, 13.16%, 25.49% and 8.03% of total area respectively. After classification, the signature for classes are validated using the benchmark outline of East Rathong glacier, India. The accuracy achieved is 89.56% with negligible variance and kappa of 0.87.
Acknowledgements
We thank the European Space Agency for the remote sensed SAR Data; we would also like to thank their Network of Resources (NoR) for providing a cloud toolbox for processing and handling the data. We thank DST, Government of India and the SERB. We thank Sikkim State Remote Sensing and Applications Centre and D. G. Shreshta, Director, Sikkim, for his continuous motivation.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/14498596.2022.2164085.