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Experiment of Automatic Glacier Extraction Methods Based on Sentinel-2 Image
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Li HUANG1, 2, 3, Zong-ren LI1, 2, 3, *, De-lin LI1, 2, 3, Rong-fang XIN1, 2, 3, Qi-ping LI1, 2, 3, Sai-la-jia WEI4
Science Technology and Engineering | 2025, 25(18) : 7710 - 7718
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Science Technology and Engineering | 2025, 25(18): 7710-7718
• Papers·Automation and Computational Technology •
Experiment of Automatic Glacier Extraction Methods Based on Sentinel-2 Image
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Li HUANG1, 2, 3, Zong-ren LI1, 2, 3, *, De-lin LI1, 2, 3, Rong-fang XIN1, 2, 3, Qi-ping LI1, 2, 3, Sai-la-jia WEI4
Affiliations
  • 1 Institute of Geological Survey of Qinghai Province, Xining 810012, China
  • 2 Qinghai Remote Sensing Big Data Engineering Technology Research Center, Xining 810012, China
  • 3 Qinghai Geological Survey Institute, The northern Qinghai-Tibet Plateau Geological Processes and Mineral Resources Laboratory, Xining 810012, China
  • 4 Geological Environment Monitoring Station of Qinghai Provincial, Xining 810001, China
Published: 2025-06-28 doi: 10.12404/j.issn.1671-1815.2405300
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Over the past half-century, global warming and humidification have led to an accelerated rate of glacier melting in China, highlighting the increasing importance of monitoring glacier distribution. However, current automated glacier extraction methods have significant limitations, such as boundary fragmentation, omission of glaciers in shaded mountain areas, and misclassification in cloud-covered regions. To address these issues, this study selected Menyuan County in Qinghai Province as the experimental area. Sentinel-2 imagery and DEM data were utilized, applying object-oriented automatic classification technology in combination with the C5.0 decision tree model to develop a multi-feature glacier extraction rule set and a neighborhood feature rule set. An improved two-stage object-oriented glacier extraction method was subsequently proposed. The findings revealed that glaciers exhibited distinct response patterns across various features, including spectral mean, spectral standard deviation, NDSI (normalized difference snow index), DEM (digital elevation model), adjacency, and slope orientation. A two-stage glacier extraction method effectively enabled automatic glacier extraction. It also significantly enhanced the recognition accuracy in cloud-covered and shaded mountain regions, achieving an overall glacier recognition accuracy of 98.50%.

Sentinel-2 image  /  decision tree  /  multi-feature combination  /  neighborhood feature  /  automatic glacier extraction
Li HUANG, Zong-ren LI, De-lin LI, Rong-fang XIN, Qi-ping LI, Sai-la-jia WEI. Experiment of Automatic Glacier Extraction Methods Based on Sentinel-2 Image[J]. Science Technology and Engineering, 2025 , 25 (18) : 7710 -7718 . DOI: 10.12404/j.issn.1671-1815.2405300
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Year 2025 volume 25 Issue 18
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doi: 10.12404/j.issn.1671-1815.2405300
  • Receive Date：2024-07-15
  • Online Date：2025-12-17
  • Published：2025-06-28
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  • Received：2024-07-15
  • Revised：2025-03-20
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Affiliations
    1 Institute of Geological Survey of Qinghai Province, Xining 810012, China
    2 Qinghai Remote Sensing Big Data Engineering Technology Research Center, Xining 810012, China
    3 Qinghai Geological Survey Institute, The northern Qinghai-Tibet Plateau Geological Processes and Mineral Resources Laboratory, Xining 810012, China
    4 Geological Environment Monitoring Station of Qinghai Provincial, Xining 810001, China
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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