Articles | Volume 17, issue 8
https://doi.org/10.5194/tc-17-3485-2023
https://doi.org/10.5194/tc-17-3485-2023
Research article
 | 
24 Aug 2023
Research article |  | 24 Aug 2023

AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini

Enze Zhang, Ginny Catania, and Daniel T. Trugman

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Latest update: 22 Nov 2024
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Short summary
Glacier termini are essential for studying why glaciers retreat, but they need to be mapped automatically due to the volume of satellite images. Existing automated mapping methods have been limited due to limited automation, lack of quality control, and inadequacy in highly diverse terminus environments. We design a fully automated, deep-learning-based method to produce termini with quality control. We produced 278 239 termini in Greenland and provided a way to deliver new termini regularly.