The effect of resolution on terrain feature extraction

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

Study Area

Publication type Conference Paper
Publication Subtype Conference Paper
Title The effect of resolution on terrain feature extraction
DOI 10.7287/peerj.preprints.27072v1
Year Published 2019
Language English
Publisher PeerJ
Contributing office(s) Center for Geospatial Information Science (CEGIS)
Description 4 p.
Larger Work Type Conference Paper
Larger Work Subtype Conference Paper
Larger Work Title Geomorphometry 2018
Conference Date August 13-17, 2018
Country United States
State California
Other Geospatial Sierra Nevada mountain range
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