An advanced deep learning framework for mapping glacial lakes and its application in the Hindu Kush-Karakoram-Himalaya region
文献类型：期刊论文
| 作者 | Zhang, Huayu1,3; Nie, Yong1,3; Liu, Linshan2; Han, Liqin4; Lyu, Qiyuan3; Wang, Wen3 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2026 |
| 卷号 | 664页码:134507 |
| 关键词 | Automated lake mapping Glacial lake changes U-Net Climate change GLOFs |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2025.134507 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | The Hindu Kush-Karakoram-Himalaya (HKH) region is highly susceptible to glacial lake outburst floods due to climate change, and the recent status and changes of glacial lakes in this region remain unclear due to limitations in data quality and traditional satellite mapping methods. In this study, we proposed a comprehensive analysis of glacial lake changes in the HKH between 2000 and 2022 using a deep-learning-based automated mapping framework. By employing a trained U-Net model and integrating cloud, shadow, snow, and topographic shadow masks, we generated high-quality glacial lake datasets with a minimum mapping unit of 0.02 km2. Compared with previous public glacial lake datasets, our dataset detects more glacial lakes, showing more comprehensive changes. Our findings reveal an increase of 325 glacial lakes and an expansion of 72.58 +/- 6.20 km2 in the lake area over the 22 years, with significant growth occurring in the eastern and central Himalayas. Ice-contact glacial lakes exhibited the most substantial area increase, driven by glacier retreat. The spatial heterogeneity in glacial lake distribution and changes reflects a response to increasing temperature, declining precipitation, and elevational gradients. Our study highlights the potential of deep learning techniques for region-scale glacial lake monitoring, providing valuable data for understanding climate impacts on high-mountain geomorphology and advancing glacial lake outburst flood risk assessments. |
| URL标识 | 查看原文 |
| WOS关键词 | HIGH-MOUNTAIN ASIA ; OUTBURST FLOODS ; TIBETAN PLATEAU ; U-NET ; LANDSAT ; CLOUD ; INVENTORY ; EXTRACTION ; EXPANSION ; NETWORK |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001614259400003 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217668]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Nie, Yong; Han, Liqin |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 101408, Peoples R China; 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 3.Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Engn Resilience, Chengdu 610299, Peoples R China; 4.Henan Normal Univ, Coll Tourism, Xinxiang 453007, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Huayu,Nie, Yong,Liu, Linshan,et al. An advanced deep learning framework for mapping glacial lakes and its application in the Hindu Kush-Karakoram-Himalaya region[J]. JOURNAL OF HYDROLOGY,2026,664:134507. |
| APA | Zhang, Huayu,Nie, Yong,Liu, Linshan,Han, Liqin,Lyu, Qiyuan,&Wang, Wen.(2026).An advanced deep learning framework for mapping glacial lakes and its application in the Hindu Kush-Karakoram-Himalaya region.JOURNAL OF HYDROLOGY,664,134507. |
| MLA | Zhang, Huayu,et al."An advanced deep learning framework for mapping glacial lakes and its application in the Hindu Kush-Karakoram-Himalaya region".JOURNAL OF HYDROLOGY 664(2026):134507. |
入库方式： OAI收割
来源：地理科学与资源研究所
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