Articles | Volume 15, issue 11
https://doi.org/10.5194/tc-15-5041-2021
https://doi.org/10.5194/tc-15-5041-2021
Research article
 | 
01 Nov 2021
Research article |  | 01 Nov 2021

Image classification of marine-terminating outlet glaciers in Greenland using deep learning methods

Melanie Marochov, Chris R. Stokes, and Patrice E. Carbonneau

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Cited articles

Alifu, H., Tateishi, R., and Johnson, B.: A new band ratio technique for mapping debris-covered glaciers using Landsat imagery and a digital elevation model, Int. J. Remote Sens., 36, 2063–2075, https://doi.org/10.1080/2150704X.2015.1034886, 2015. 
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Short summary
Research into the use of deep learning for pixel-level classification of landscapes containing marine-terminating glaciers is lacking. We adapt a novel and transferable deep learning workflow to classify satellite imagery containing marine-terminating outlet glaciers in Greenland. Our workflow achieves high accuracy and mimics human visual performance, potentially providing a useful tool to monitor glacier change and further understand the impacts of climate change in complex glacial settings.