Articles | Volume 17, issue 8
https://doi.org/10.5194/tc-17-3485-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-3485-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Aug 2023
Research article |
| 24 Aug 2023
| 24 Aug 2023
AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini
Institute of Geophysics, The University of Texas, Austin, TX 78758, USA
Ginny Catania
Institute of Geophysics, The University of Texas, Austin, TX 78758, USA
Department of Geological Sciences, The University of Texas, Austin, TX 78712, USA
Daniel T. Trugman
Nevada Seismological Laboratory, University of Reno, Nevada, NV 89557, USA
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Cited
17 citations as recorded by crossref.
- Multi-temporal calving front segmentation M. Dreier et al. https://doi.org/10.1016/j.isprsjprs.2026.05.053
- Advances in monitoring glaciological processes in Kalallit Nunaat (Greenland) over the past decades D. Fahrner et al. https://doi.org/10.1371/journal.pclm.0000379
- Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning N. Gourmelon et al. https://doi.org/10.1109/TPAMI.2026.3685700
- Calving front monitoring at a subseasonal resolution: a deep learning application for Greenland glaciers E. Loebel et al. https://doi.org/10.5194/tc-18-3315-2024
- A Scoping Review of Automated Calving Front Detection in Satellite Images and Calving Front Position Datasets W. Milczarek et al. https://doi.org/10.3390/rs18070969
- Compounding sub-seasonal variations in Greenland outlet glacier dynamics revealed by high-resolution observations E. Zhang et al. https://doi.org/10.5194/tc-20-3875-2026
- A Novel Approach to Automated Mapping Subweekly Calving Front of Petermann Glacier (2016–2023)—Using Sentinel-2 Satellite Data and Segment Anything Model (SAM) D. Li et al. https://doi.org/10.1109/JSTARS.2025.3573496
- The Greenland Ice-Marginal Lake Inventory Series from 2016 to 2023 P. How et al. https://doi.org/10.5194/essd-17-6331-2025
- Ice front positions for Greenland glaciers (2002–2021): a spatially extensive seasonal record and benchmark dataset for algorithm validation X. Lu et al. https://doi.org/10.5194/essd-18-2635-2026
- Horizontal force-balance calving laws: Ice shelves, marine- and land-terminating glaciers N. Coffey & C. Lai https://doi.org/10.1017/jog.2025.10068
- Interannual Glacier Variability and Accelerated Albedo Decline in Northeastern Tibetan Plateau: Multidecadal Remote Sensing Insights (1986–2024) X. Zhao et al. https://doi.org/10.1109/JSTARS.2026.3718486
- AMD-HookNet++: Evolution of AMD-HookNet With Hybrid CNN–Transformer Feature Enhancement for Glacier Calving Front Segmentation F. Wu et al. https://doi.org/10.1109/TGRS.2025.3642764
- Calving front positions for 42 key glaciers of the Antarctic Peninsula Ice Sheet: a sub-seasonal record from 2013 to 2023 based on deep-learning application to Landsat multi-spectral imagery E. Loebel et al. https://doi.org/10.5194/essd-17-65-2025
- SSL4SAR: Self-Supervised Learning for Glacier Calving Front Extraction From SAR Imagery N. Gourmelon et al. https://doi.org/10.1109/TGRS.2025.3580945
- A high-resolution calving front data product for marine-terminating glaciers in Svalbard T. Li et al. https://doi.org/10.5194/essd-16-919-2024
- Outlet glacier seasonal terminus prediction using interpretable machine learning K. Shionalyn et al. https://doi.org/10.5194/tc-20-1725-2026
- Seasonal changes of mélange thickness coincide with Greenland calving dynamics Y. Meng et al. https://doi.org/10.1038/s41467-024-55241-7
17 citations as recorded by crossref.
- Multi-temporal calving front segmentation M. Dreier et al. https://doi.org/10.1016/j.isprsjprs.2026.05.053
- Advances in monitoring glaciological processes in Kalallit Nunaat (Greenland) over the past decades D. Fahrner et al. https://doi.org/10.1371/journal.pclm.0000379
- Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning N. Gourmelon et al. https://doi.org/10.1109/TPAMI.2026.3685700
- Calving front monitoring at a subseasonal resolution: a deep learning application for Greenland glaciers E. Loebel et al. https://doi.org/10.5194/tc-18-3315-2024
- A Scoping Review of Automated Calving Front Detection in Satellite Images and Calving Front Position Datasets W. Milczarek et al. https://doi.org/10.3390/rs18070969
- Compounding sub-seasonal variations in Greenland outlet glacier dynamics revealed by high-resolution observations E. Zhang et al. https://doi.org/10.5194/tc-20-3875-2026
- A Novel Approach to Automated Mapping Subweekly Calving Front of Petermann Glacier (2016–2023)—Using Sentinel-2 Satellite Data and Segment Anything Model (SAM) D. Li et al. https://doi.org/10.1109/JSTARS.2025.3573496
- The Greenland Ice-Marginal Lake Inventory Series from 2016 to 2023 P. How et al. https://doi.org/10.5194/essd-17-6331-2025
- Ice front positions for Greenland glaciers (2002–2021): a spatially extensive seasonal record and benchmark dataset for algorithm validation X. Lu et al. https://doi.org/10.5194/essd-18-2635-2026
- Horizontal force-balance calving laws: Ice shelves, marine- and land-terminating glaciers N. Coffey & C. Lai https://doi.org/10.1017/jog.2025.10068
- Interannual Glacier Variability and Accelerated Albedo Decline in Northeastern Tibetan Plateau: Multidecadal Remote Sensing Insights (1986–2024) X. Zhao et al. https://doi.org/10.1109/JSTARS.2026.3718486
- AMD-HookNet++: Evolution of AMD-HookNet With Hybrid CNN–Transformer Feature Enhancement for Glacier Calving Front Segmentation F. Wu et al. https://doi.org/10.1109/TGRS.2025.3642764
- Calving front positions for 42 key glaciers of the Antarctic Peninsula Ice Sheet: a sub-seasonal record from 2013 to 2023 based on deep-learning application to Landsat multi-spectral imagery E. Loebel et al. https://doi.org/10.5194/essd-17-65-2025
- SSL4SAR: Self-Supervised Learning for Glacier Calving Front Extraction From SAR Imagery N. Gourmelon et al. https://doi.org/10.1109/TGRS.2025.3580945
- A high-resolution calving front data product for marine-terminating glaciers in Svalbard T. Li et al. https://doi.org/10.5194/essd-16-919-2024
- Outlet glacier seasonal terminus prediction using interpretable machine learning K. Shionalyn et al. https://doi.org/10.5194/tc-20-1725-2026
- Seasonal changes of mélange thickness coincide with Greenland calving dynamics Y. Meng et al. https://doi.org/10.1038/s41467-024-55241-7
Saved (final revised paper)
Latest update: 08 Sep 2026
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.
Glacier termini are essential for studying why glaciers retreat, but they need to be mapped...
