Mapping debris-covered glaciers and identifying factors affecting the accuracy

Supraglacial debris significantly hampers the mapping of glaciers using remote sensing data. A semi-automated approach for the mapping of debris-covered glacier was applied, which combined the inputs from thermal and optical remote sensing data and the Digital Elevation Model (DEM) derived morphometric parameters. A thermal mask that delineates the supraglacial debris extent was generated by the thresholding of surface temperature layer obtained from Landsat TM/ETM + thermal band satellite data. The extent of clean glacier ice was identified by band ratioing and thresholding of TM/ETM + 4 and TM/ETM + 5 bands. Morphometric parameters like slope, plan curvature and profile curvature were rearranged in similar surface groups using the technique of cluster analysis. All these masks were vectorized and final classification maps were generated using geographic information system (GIS) overlay operations. The areal extent of semi-automated outlines of Hamtah and Patsio Glaciers derived from cluster analysis varied from manually derived outline using pan-sharpened Landsat ETM + September 2000 image by − 1.3% and − 1.6%, respectively. Year 2011 classification map for Patsio Glacier was compared with the field observations and a high correlation and overall accuracy (~ 91%) were observed. The same classification methodology was adopted for images of years 2000 and 1989 for Patsio Glacier to observe the effects of varying snow cover patterns on adopted methodology. Also the methodology was adopted and verified for Hamtah Glacier, with different geometry and terrain conditions as compared to Patsio Glacier. Although the spatial resolution limitation of ASTER GDEM and Landsat TM/ETM + thermal band limits the automated mapping of small debris-covered glaciers, the outcomes are still favorable enough to apply such methodologies for mapping different types of debris-covered glaciers in the future.