Modelling Glacier Dynamics and Sea Level Rise for Future Projections in the Gulf of Alaska

In the last few years, there has been a significant change in the sea level of Alaska by the melting of glaciers, due to which the flora and fauna in the coastal region have been endangered. Accurate prediction and analysis of change in sea level is crucial for the policymakers and protective agencies to take proper measures against the change. Existing studies don't properly predict the changes in the glacier mass, glacier health or the changes in the sea level. The main problem lies in the unavailability of data. This research provides a deep analysis of glacier mass change from 1985-2021 extracted from a remote sensing timelapse video, and it predicts the changes in glacier health and sea level from 2021-2026. This solution uses various image processing techniques to extract data from the video's image sequence and uses the LSTM and RNN models ensembled together to predict future changes with an accuracy of 80%. This prediction provides a solution for various policy-building organisations to be ready for a change in habitat.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/icctdc64446.2025.11158823
Primary Topic
Cryospheric studies and observations
Type
article
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Modelling Glacier Dynamics and Sea Level Rise for Future Projections in the Gulf of Alaska

Piyush Jaiswal, Tannisha Kundu, Roumo Kundu, Taha Fatma et al.
Cryospheric studies and observations
article

Modelling Glacier Dynamics and Sea Level Rise for Future Projections in the Gulf of Alaska

Piyush Jaiswal, Tannisha Kundu, Roumo Kundu, Taha Fatma, S. M. Gupta, Harsh Mahanti
article en

Abstract

In the last few years, there has been a significant change in the sea level of Alaska by the melting of glaciers, due to which the flora and fauna in the coastal region have been endangered. Accurate prediction and analysis of change in sea level is crucial for the policymakers and protective agencies to take proper measures against the change. Existing studies don't properly predict the changes in the glacier mass, glacier health or the changes in the sea level. The main problem lies in the unavailability of data. This research provides a deep analysis of glacier mass change from 1985-2021 extracted from a remote sensing timelapse video, and it predicts the changes in glacier health and sea level from 2021-2026. This solution uses various image processing techniques to extract data from the video's image sequence and uses the LSTM and RNN models ensembled together to predict future changes with an accuracy of 80%. This prediction provides a solution for various policy-building organisations to be ready for a change in habitat.

Systems, Applications & Products in Data Processing (United Kingdom) (GB)
Openalex Percentile: Top 69%
Cryospheric studies and observations
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