1. Introduction
The best natural indicator of ongoing climate change is a temporal analysis of changes of mountain glaciers [1],[2],[3]. Glacier segmentation is a prerequisite for monitoring global climate change, global warming, water resources, glacial hazards and many other important life saving tasks [4]. Segmentation of Glaciers is a very trivial task in remote sensing. Glaciers consist of two main parts; the clean white portion and the debris covered portion which mostly resembles the surrounding rocks. Different methods have been adopted for this purpose using satellite imagery. Multi spectral Satellite images from Thematic Mapper (TM) sensor of the Landsat Satellite are often used for the purpose of delineating glaciers [5]. General categories of glacier delineation are described in [6]. The methods used for Glacier classification can be broadly grouped into 5 categories namely False Colour Composites (FCCs) from Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) digital data, glacier mapping with TM by manual delineation of the glacier outline, segmentation of ratio images with reflectance thresholds, different supervised classification techniques and calculation of glacier reflection with TM and the comparison with ground measurements.