Fast, reliable and accurate methods for glacier mapping are necessary for understanding glacier dynamics and evolution and assessing their response to climate change. Conventional semi-automatic approaches are based on medium-resolution satellite images, but their use can cause significant loss of accuracy when analyzing small glaciers, which are predominant in the Alps. In this paper, we present a semi-automatic segmentation approach based on very high-resolution visible RGB images acquired from a UAV (Unmanned Aerial Vehicle) survey of the Fomi Glacier, in the Italian Alps, using an off-the-shelf digital camera. The method has the ability to map large-scale morphological features, i.e. bare ice and medial moraines, with better accuracy than methods relying on medium-resolution satellite imagery, with only slight misclassification at the margins. By using segmentation, we also mapped small-scale morphologies not discernible on satellite images, including epiglacial lakes and snow patches, in a semi-automatic way. On a small portion of the eastern ablation tongue, featuring homogeneous illumination conditions, we also investigated in finer detail the occurrence of fine and sparse debris and tested a texture filter technique for mapping crevasses, which showed promising results. Our analyses confirm that the glacier is undergoing intense dynamic processes, including darkening of the ablation tongue and increased surface instability, and show the potential of UAVs to revolutionize glaciological studies. We suggest that by using a combination of different payloads, mapping of glacier features via UAVs could reach high levels of accuracy and speed, making them useful tools for glacier inventories and geomorphological maps
