Cheung et al. (2026) Expanding Temporal Glacier Observations Through Machine Learning and Multispectral Imagery Datasets in the Canadian Arctic Archipelago: A Decadal Snowline Analysis (2013–2024)

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-03-11
• Authors: Wai Yin (Wilson) Cheung, Laura Thomson
• DOI: 10.3390/rs18060864

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study presents the first decadal (2013–2024) satellite-derived time series of late-summer snowline altitude (SLA) for six Canadian Arctic Archipelago (CAA) glaciers, revealing that annual peak SLA correlates positively with summer warmth and that glacier hypsometry strongly modulates climatic sensitivity.

Objective

• To generate the first decadal (2013–2024) satellite-derived time series of late-summer snowline altitude (SLA) for six glaciers in the Canadian Arctic Archipelago (CAA) and characterize their response to melt-season forcing.

Study Configuration

• Spatial Scale: Six glaciers within the Canadian Arctic Archipelago (CAA), including White Glacier, Highway Glacier, Turner Glacier, and BylotD20s.
• Temporal Scale: Decadal (2013–2024) for SLA time series; meteorological records also considered.

Methodology and Data

• Models used:
  • Machine learning for mapping glacier surface cover types (snow and bare ice).
  • Elevation-binning method for SLA extraction.
  • Snow-Elevation Histogram Analysis (SEHA) for SLA extraction.
• Data sources:
  • Satellite: 9920 Landsat 8/9 and Sentinel-2 scenes.
  • Observation: Equilibrium-line altitude (ELA) observations from White Glacier for validation.
  • Reanalysis/Elevation: ArcticDEM v3 for elevation data.
  • Meteorological: Positive degree days (PDD) from Eureka, Pond Inlet, and Pangnirtung stations.

Main Results

• A decadal (2013–2024) satellite-derived time series of late-summer snowline altitude (SLA) was established for six CAA glaciers.
• All glaciers exhibit a characteristic seasonal snow-covered area (SCA) cycle: maximum extent in June, minimum in August, and partial recovery in September, with extreme anomalies observed in 2020.
• Annual peak SLA correlates positively with summer warmth.
• Sensitivities of SLA to positive degree days (PDD) were quantified: 2.56 m (°C d)−1 for White Glacier, 0.67 m (°C d)−1 for Highway Glacier, and 0.83 m (°C d)−1 for Turner Glacier.
• Glacier hypsometry strongly modulates climatic sensitivity; glaciers with limited high-elevation areas (e.g., BylotD20s, Turner) frequently lose their accumulation zones in warm years.
• At White Glacier, the elevation-bin method replicated interannual ELA variability with high correlation and lower error (mean bias +53 m; RMSE 177 m) compared to SEHA (+165 m; 339 m).
• Meteorological records indicate significant summer and winter warming at Eureka, with increasing PDD, while precipitation trends are spatially variable.

Contributions

• Presents the first decadal (2013–2024) satellite-derived time series of late-summer snowline altitude (SLA) for glaciers in the Canadian Arctic Archipelago, addressing a significant data gap.
• Develops and validates a regionally calibrated, quality-assured elevation-bin method, providing an objective and transferable approach for SLA time series generation and ELA estimation in data-sparse Arctic environments.
• Quantifies the relationship between SLA and summer warmth (PDD) and highlights the critical role of glacier hypsometry in modulating climatic sensitivity, emphasizing increasing stress on accumulation zones under continued warming.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Cheung2026Expanding,
  author = {Cheung, Wai Yin (Wilson) and Thomson, Laura},
  title = {Expanding Temporal Glacier Observations Through Machine Learning and Multispectral Imagery Datasets in the Canadian Arctic Archipelago: A Decadal Snowline Analysis (2013–2024)},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18060864},
  url = {https://doi.org/10.3390/rs18060864}
}