Articles | Volume 16, issue 10
https://doi.org/10.5194/tc-16-4273-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-4273-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Oct 2022
Research article |
| 13 Oct 2022
| 13 Oct 2022
Glacier extraction based on high-spatial-resolution remote-sensing images using a deep-learning approach with attention mechanism
Xinde Chu
College of Geography and Environmental Science, Northwest Normal
University, Lanzhou, 730070, China
Xiaojun Yao
CORRESPONDING AUTHOR
College of Geography and Environmental Science, Northwest Normal
University, Lanzhou, 730070, China
Hongyu Duan
College of Geography and Environmental Science, Northwest Normal
University, Lanzhou, 730070, China
Cong Chen
Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
Jing Li
College of Geography and Environmental Science, Northwest Normal
University, Lanzhou, 730070, China
Wenlong Pang
Xining Center of Natural Resources Comprehensive Survey, China
Geological Survey, Xining, 810000, China
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Cited
16 citations as recorded by crossref.
- Vegetation extraction from Landsat8 operational land imager remote sensing imagery based on Attention U-Net and vegetation spectral features J. Zhang et al. 10.1117/1.JRS.18.032403
- Extraction of Cladophora Blooms in Qinghai Lake Through the Integration of Sentinel-2 MSI Imagery and Deep Learning Techniques J. Zhang et al. 10.1109/JSTARS.2024.3447886
- Mapping taluses using deep learning and high-resolution satellite images D. Jiang et al. 10.1080/17538947.2025.2484466
- A Lightweight Winter Wheat Planting Area Extraction Model Based on Improved DeepLabv3+ and CBAM Y. Zhang et al. 10.3390/rs15174156
- A dataset of glacier inventory in four Central Asian countries during 2022–2023 Z. GUO et al. 10.11922/11-6035.csd.2024.0151.zh
- Mapping Debris-Covered Glaciers Using High-Resolution Imagery (GF-2) and Deep Learning Algorithms X. Yang et al. 10.3390/rs16122062
- AMD-HookNet for Glacier Front Segmentation F. Wu et al. 10.1109/TGRS.2023.3245419
- The research on landslide detection in remote sensing images based on improved DeepLabv3+ method Y. Li 10.1038/s41598-025-92822-y
- Glacier Area and Surface Flow Velocity Variations for 2016–2024 in the West Kunlun Mountains Based on Time-Series Sentinel-2 Images D. Jiang et al. 10.3390/rs17071290
- Remote Sensing and Modeling of the Cryosphere in High Mountain Asia: A Multidisciplinary Review Q. Ye et al. 10.3390/rs16101709
- Updating glacier inventories on the periphery of Antarctica and Greenland using multi-source data X. Liu et al. 10.1017/aog.2023.75
- A new inventory and future projections of thermokarst lakes in the permafrost regions of the Qilian Mountains, northeastern Qinghai-Tibet Plateau, China W. Tian et al. 10.1016/j.geomorph.2024.109348
- Automated glacier extraction using a Transformer based deep learning approach from multi-sensor remote sensing imagery Y. Peng et al. 10.1016/j.isprsjprs.2023.06.015
- GLA-STDeepLab: SAR Enhancing Glacier and Ice Shelf Front Detection Using Swin-TransDeepLab With Global–Local Attention Q. Zhu et al. 10.1109/TGRS.2023.3324404
- SAU-Net: A Deep Learning Approach for Glacier Mapping Based on Multisource Remote Sensing Data Y. Xiang et al. 10.1109/ACCESS.2025.3542834
- Analysis of continuous calving front retreat and the associated influencing factors of the Thwaites Glacier using high-resolution remote sensing data from 2015 to 2023 Q. Zhu et al. 10.1080/17538947.2024.2390438
16 citations as recorded by crossref.
- Vegetation extraction from Landsat8 operational land imager remote sensing imagery based on Attention U-Net and vegetation spectral features J. Zhang et al. 10.1117/1.JRS.18.032403
- Extraction of Cladophora Blooms in Qinghai Lake Through the Integration of Sentinel-2 MSI Imagery and Deep Learning Techniques J. Zhang et al. 10.1109/JSTARS.2024.3447886
- Mapping taluses using deep learning and high-resolution satellite images D. Jiang et al. 10.1080/17538947.2025.2484466
- A Lightweight Winter Wheat Planting Area Extraction Model Based on Improved DeepLabv3+ and CBAM Y. Zhang et al. 10.3390/rs15174156
- A dataset of glacier inventory in four Central Asian countries during 2022–2023 Z. GUO et al. 10.11922/11-6035.csd.2024.0151.zh
- Mapping Debris-Covered Glaciers Using High-Resolution Imagery (GF-2) and Deep Learning Algorithms X. Yang et al. 10.3390/rs16122062
- AMD-HookNet for Glacier Front Segmentation F. Wu et al. 10.1109/TGRS.2023.3245419
- The research on landslide detection in remote sensing images based on improved DeepLabv3+ method Y. Li 10.1038/s41598-025-92822-y
- Glacier Area and Surface Flow Velocity Variations for 2016–2024 in the West Kunlun Mountains Based on Time-Series Sentinel-2 Images D. Jiang et al. 10.3390/rs17071290
- Remote Sensing and Modeling of the Cryosphere in High Mountain Asia: A Multidisciplinary Review Q. Ye et al. 10.3390/rs16101709
- Updating glacier inventories on the periphery of Antarctica and Greenland using multi-source data X. Liu et al. 10.1017/aog.2023.75
- A new inventory and future projections of thermokarst lakes in the permafrost regions of the Qilian Mountains, northeastern Qinghai-Tibet Plateau, China W. Tian et al. 10.1016/j.geomorph.2024.109348
- Automated glacier extraction using a Transformer based deep learning approach from multi-sensor remote sensing imagery Y. Peng et al. 10.1016/j.isprsjprs.2023.06.015
- GLA-STDeepLab: SAR Enhancing Glacier and Ice Shelf Front Detection Using Swin-TransDeepLab With Global–Local Attention Q. Zhu et al. 10.1109/TGRS.2023.3324404
- SAU-Net: A Deep Learning Approach for Glacier Mapping Based on Multisource Remote Sensing Data Y. Xiang et al. 10.1109/ACCESS.2025.3542834
- Analysis of continuous calving front retreat and the associated influencing factors of the Thwaites Glacier using high-resolution remote sensing data from 2015 to 2023 Q. Zhu et al. 10.1080/17538947.2024.2390438
Latest update: 18 Apr 2025
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.
The available remote-sensing data are increasingly abundant, and the efficient and rapid...
