Glaciers are important and sensitive part of our environment which can be used as indicator of global warming and climate change. Glacier facies represent distinct regions of a glacier surface characterized by near surface structure and density that develop as a function of spatial variations in surface melt and accumulation. The facies mapping aids in delineating different zones of the glacier, which are useful in computing glacier mass balance and modeling. In this study we tested traditional and advanced classification techniques on the Edithbreen glacier situated in Ny-lesund, Svalbard, using WorldView-3 and Landsat 8 OLI. The comparison of the accuracy was conducted using error matrices. Six measures of accuracy were derived from the error matrices and were compared with each other to find the method delivering the most adequate output for facies mapping. The pixel-based approach applied to Landsat-8 data yielded higher accuracies (>80%) when compared to that. The object-oriented classification revealed a much better accuracy and high kappa coefficient for both low and high-resolution datasets. The study clearly indicates that the object-oriented classification provides better results for glacier facies classification when high spatial resolution is used, but for lower spatial resolution, pixel-based methods are adequate.

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