Efficiency of artificial neural networks for glacier ice-thickness estimation: a case study in western Himalaya, India
Knowledge of glacier volume is crucial for ice flow modelling and predicting the impacts of climate change on glaciers. Rugged terrain, harsh weather conditions and logistic costs limit field-based ice thickness observations in the Himalaya. Remote-sensing applications, together with mathematical mo...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Cambridge University Press
2021-08-01
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Series: | Journal of Glaciology |
Subjects: | |
Online Access: | https://www.cambridge.org/core/product/identifier/S0022143021000198/type/journal_article |