The effect of resolution on terrain feature extraction

13 Abstract—Recent increase in the production of high-resolution 14 digital elevation models (DEMs) from lidar data has led to interest 15 in their use for terrain mapping. Although the impact of different 16 resolutions has been studied relative to terrain characteristics like 17 roughness, slope and curvature, its relationship to the extraction of 18 terrain features remains unclear. To address this question, this study 19 tests the impact of four resolutions on the capture of glacial cirques 20 from DEMs. Mean curvature was derived from one arc-second, one21 third arc-second, one-ninth arc-second and half meter DEMs 22 representing a cirque-covered mountainous region southwest of 23 Lake Tahoe, California. Using a GEOBIA workflow, ridge objects 24 were identified, and three scales via the multi-resolution scale 25 parameter (SP) of objects bordering the ridges were classified as 26 cirque objects. The resulting classifications were compared to 27 reference cirques digitized at a scale of ~1:10,000. Results show that 28 the one-third arc-second DEM produces the set of cirque objects 29 most closely resembling the reference cirques. The one-ninth arc30 second DEM afforded the second-best classification. These results 31 emphasize the importance in carefully choosing resolution relative 32 to the features extracted, rather than using the highest resolution 33 data available. In the case of GEOBIA workflows, the choice of scale 34 parameter is equally important. 35