{"date_published":"2018-05-31T00:00:00Z","author":[{"last_name":"Herreid","full_name":"Herreid, Sam","first_name":"Sam"},{"first_name":"Francesca","full_name":"Pellicciotti, Francesca","last_name":"Pellicciotti","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"}],"abstract":[{"text":"Ice cliffs within a supraglacial debris cover have been identified as a source for high ablation relative to the surrounding debris-covered area. Due to their small relative size and steep orientation, ice cliffs are difficult to detect using nadir-looking space borne sensors. The method presented here uses surface slopes calculated from digital elevation model (DEM) data to map ice cliff geometry and produce an ice cliff probability map. Surface slope thresholds, which can be sensitive to geographic location and/or data quality, are selected automatically. The method also attempts to include area at the (often narrowing) ends of ice cliffs which could otherwise be neglected due to signal saturation in surface slope data. The method was calibrated in the eastern Alaska Range, Alaska, USA, against a control ice cliff dataset derived from high-resolution visible and thermal data. Using the same input parameter set that performed best in Alaska, the method was tested against ice cliffs manually mapped in the Khumbu Himal, Nepal. Our results suggest the method can accommodate different glaciological settings and different DEM data sources without a data intensive (high-resolution, multi-data source) recalibration.","lang":"eng"}],"article_type":"original","language":[{"iso":"eng"}],"keyword":["Earth-Surface Processes","Water Science and Technology"],"article_processing_charge":"No","_id":"12606","issue":"5","publication_status":"published","volume":12,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"1811-1829","publication_identifier":{"issn":["1994-0424"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5194/tc-12-1811-2018"}],"date_created":"2023-02-20T08:13:36Z","date_updated":"2023-02-28T11:39:26Z","extern":"1","quality_controlled":"1","publication":"The Cryosphere","month":"05","oa":1,"intvolume":" 12","oa_version":"Published Version","scopus_import":"1","title":"Automated detection of ice cliffs within supraglacial debris cover","doi":"10.5194/tc-12-1811-2018","year":"2018","citation":{"ieee":"S. Herreid and F. Pellicciotti, “Automated detection of ice cliffs within supraglacial debris cover,” The Cryosphere, vol. 12, no. 5. Copernicus Publications, pp. 1811–1829, 2018.","chicago":"Herreid, Sam, and Francesca Pellicciotti. “Automated Detection of Ice Cliffs within Supraglacial Debris Cover.” The Cryosphere. Copernicus Publications, 2018. https://doi.org/10.5194/tc-12-1811-2018.","short":"S. Herreid, F. Pellicciotti, The Cryosphere 12 (2018) 1811–1829.","apa":"Herreid, S., & Pellicciotti, F. (2018). Automated detection of ice cliffs within supraglacial debris cover. The Cryosphere. Copernicus Publications. https://doi.org/10.5194/tc-12-1811-2018","ista":"Herreid S, Pellicciotti F. 2018. Automated detection of ice cliffs within supraglacial debris cover. The Cryosphere. 12(5), 1811–1829.","ama":"Herreid S, Pellicciotti F. Automated detection of ice cliffs within supraglacial debris cover. The Cryosphere. 2018;12(5):1811-1829. doi:10.5194/tc-12-1811-2018","mla":"Herreid, Sam, and Francesca Pellicciotti. “Automated Detection of Ice Cliffs within Supraglacial Debris Cover.” The Cryosphere, vol. 12, no. 5, Copernicus Publications, 2018, pp. 1811–29, doi:10.5194/tc-12-1811-2018."},"type":"journal_article","publisher":"Copernicus Publications","status":"public","day":"31"}