Mapping of debris-covered glaciers using remote-sensing techniques is recognized as one of the greatest challenges for generating glacier inventories and automated glacier change analysis. The use of visible (VIS) and near-infrared (NIR) bands does not provide sufficient continual information to detect debris-covered ice with remote-sensing data. This article presents a semi-automated mapping method for the debris-covered glaciers of the Garhwal Himalayas based on an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model (DEM) and thermal data. Morphometric parameters such as slope, plan curvature and profile curvature were computed by means of the ASTER DEM and organized in similar surface groups using cluster analysis. A thermal mask was generated from a single band of an ASTER thermal image, while the clean-ice glaciers were identified using a band ratio based on ASTER bands 3 and 4. Vector maps were drawn up from the output of the cluster analysis, the thermal mask and the band ratio mask for the preparation of the final outlines of the debris-covered glaciers using geographic information system (GIS) overlay operations. The semi-automated mapped debris-covered glacier outline of Gangotri Glacier derived from 2006 ASTER data varied by about 5% from the manually outlined debris-covered glacier area of the Cartosat-1 high-resolution image from the same year. By contrast, outlines derived from the method developed using the 2001 ASTER DEM and Landsat thermal data varied by only 0.5% from manually digitized outlines based on Indian Remote Sensing Satellite (IRS)-1C panchromatic (PAN) data. We found that post-depositional sedimentation by debris flow/mass movement was a great hindrance in the fully automated mapping of debris-covered glaciers in the polygenetic environment of the Himalayas. In addition, the resolution of ASTER stereo data and thermal band data limits the automated mapping of small debris-covered glaciers with adjacent end moraine. However, the results obtained for Gangotri Glacier confirm the strong potential of the approach presented.