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

E Zhang, G Catania, DT Trugman - The Cryosphere, 2023 - tc.copernicus.org
Ice sheet marine margins via outlet glaciers are susceptible to climate change and are
expected to respond through retreat, steepening, and acceleration, although with significant …

Pervasive glacier retreats across Svalbard from 1985 to 2023

T Li, S Hofer, G Moholdt, A Igneczi, K Heidler… - Nature …, 2025 - nature.com
A major uncertainty in predicting the behaviour of marine-terminating glaciers is ice
dynamics driven by non-linear calving front retreat, which is poorly understood and …

[HTML][HTML] Calving front monitoring at a subseasonal resolution: a deep learning application for Greenland glaciers

E Loebel, M Scheinert, M Horwath, A Humbert… - The …, 2024 - tc.copernicus.org
The mass balance of the Greenland Ice Sheet is strongly influenced by the dynamics of its
outlet glaciers. Therefore, it is of paramount importance to accurately and continuously …

CS-GAC: Compressively sensed geodesic active contours

H Shan - Pattern Recognition, 2024 - Elsevier
This paper proposes an edge based compressively sensed (CS) geodesic active contour
(GAC) model, termed CS-GAC, to ensure faithful edge detection and accurate object …

Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning

N Gourmelon, K Heidler, E Loebel, D Cheng… - arxiv preprint arxiv …, 2025 - arxiv.org
Calving front position variation of marine-terminating glaciers is an indicator of ice mass loss
and a crucial parameter in numerical glacier models. Deep Learning (DL) systems can …