On the transferability of rule sets for mapping cirques using Object-based feature extraction

Cirques are complex landforms resulting from glacial erosion and occur in the mountains of western Austria at various topographic levels. After deglaciation they may potentially hold climate proxies, are showcases of vegetation regrowth and play an important role in the regulation of mountain hydrology. Our objective is to develop a workflow to test an object‐based rule‐set that decomposes LiDAR DEMs into the main cirque components: divide, cirque headwall, cirque floor and into the sub‐component cirque lake by using stratified segmentation and classification. One cirque cluster was used to train the classification settings, which were tested in a second cirque cluster. Classification results and accuracy of both clusters were compared. We conclude that the transferability of rule sets for the extraction of cirque components is promising, but that younger depositional and erosional landforms may influence correct cirque component extraction. Fine‐tuning of rule sets and integration of additional data is necessary to discriminate cirques moraines and cirque thresholds, as these sub‐components highly depend on variations in local cirque development.