Articles | Volume 16, issue 10
The Cryosphere, 16, 4273–4289, 2022
https://doi.org/10.5194/tc-16-4273-2022
The Cryosphere, 16, 4273–4289, 2022
https://doi.org/10.5194/tc-16-4273-2022
Research article
13 Oct 2022
Research article | 13 Oct 2022

Glacier extraction based on high-spatial-resolution remote-sensing images using a deep-learning approach with attention mechanism

Xinde Chu et al.

Data sets

Glacier coverage data on the Tibetan Plateau in 2017 (TPG2017, Version1.0) Q. H. Ye https://doi.org/10.11888/Glacio.tpdc.270924

Model code and software

yiyou101/Attention-DeepLab-V3plus: A deep learning approach to extract the glacier outlines (v2.1) Xinde Chu https://doi.org/10.5281/zenodo.7132888

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Short summary
The available remote-sensing data are increasingly abundant, and the efficient and rapid acquisition of glacier boundaries based on these data is currently a frontier issue in glacier research. In this study, we designed a complete solution to automatically extract glacier outlines from the high-resolution images. Compared with other methods, our method achieves the best performance for glacier boundary extraction in parts of the Tanggula Mountains, Kunlun Mountains and Qilian Mountains.