C004-0016
IcePicks: a collaborative database and toolset for identifying Greenland outlet glacier termini

Monday, 7 December 2020
Poster
Sophie A Goliber, University of Texas at Austin, Institute for Geophysics, Geological Sciences, Austin, TX, United States, Taryn E Black, University of Washington, Earth and Space Sciences, Seattle, WA, United States; Applied Physics Laboratory University of Washington, Seattle, WA, United States, James Lea, University of Liverpool, School of Environmental Sciences, Liverpool, United Kingdom, Daniel Lop-Chi Cheng, University of California Irvine, Irvine, CA, United States and Ginny A Catania, University of Texas at Austin, Austin, TX, United States; University of Texas, Institute for Geophysics, Austin, TX, United States
Abstract:
Marine-terminating outlet glacier terminus traces, mapped from satellite and aerial imagery, have been used extensively in understanding how outlet glaciers adjust to climatic changes over a range of time scales in the Greenland Ice Sheet. Numerous studies have digitized termini manually, but this process is labor intensive, no general methodology exists, and lack of coordination leads to duplication of efforts. Additionally, machine learning techniques are rapidly making progress in their ability to accurately automate the extraction of glacier termini, with promising developments across a number of optical and SAR satellite sensors. However, further high quality manually-digitized terminus traces are needed to create training data for robust automatic picks. Here we present efforts to produce a database of manually digitized terminus picks and an inter-comparison of picking techniques to determine errors and best practices for future efforts in digitization. These data have been cleaned, associated with appropriate metadata and image scenes, and compiled so they can be easily accessed by scientists. A new version of The Google Earth Engine Digitization Tool (GEEDiT) has been developed specifically for future manual picking of the Greenland Ice sheet to create more training data as needed. Data will be released for use in machine learning methods and for glaciological studies in 2021. Data can be submitted to this project and a list of current contributors can both be found at http://www.catania-ice.org/icepicks.