A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway

The water dynamics of barrier lakes in high mountain areas are crucial for risk assessment, disaster prediction, safety management, and decision-making. Objective and Methods To accurately and efficiently extract the water boundaries of mountainous barrier lakes, this paper focuses on the Attabad ba...

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Main Authors: Yousan LI, Guangchao CAO, Meiliang ZHAO, Wenqian YE, Wanqiang QI, Hongkui YANG, Yuanzhao WU, Qiang GU, Yuguo LU, Shilin WANG
Format: Article
Language:zho
Published: Editorial Department of Bulletin of Geological Science and Technology 2024-11-01
Series:地质科技通报
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Online Access:https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20240125
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author Yousan LI
Guangchao CAO
Meiliang ZHAO
Wenqian YE
Wanqiang QI
Hongkui YANG
Yuanzhao WU
Qiang GU
Yuguo LU
Shilin WANG
author_facet Yousan LI
Guangchao CAO
Meiliang ZHAO
Wenqian YE
Wanqiang QI
Hongkui YANG
Yuanzhao WU
Qiang GU
Yuguo LU
Shilin WANG
author_sort Yousan LI
collection DOAJ
description The water dynamics of barrier lakes in high mountain areas are crucial for risk assessment, disaster prediction, safety management, and decision-making. Objective and Methods To accurately and efficiently extract the water boundaries of mountainous barrier lakes, this paper focuses on the Attabad barrier lake along the Karakoram Highway, proposing a water extraction method based on decision tree classification. This method incorporates slope information into six conventional water extraction methods for decision tree classification. The effectiveness of these six methods was compared for extracting water from barrier lakes in the experimental area. The best-performing methods suitable for barrier lakes in high-altitude areas were applied to extract the water body range of the Attabad barrier lake.Accuracy was assessed using a confusion matrix, and classification post-processing was performed to refine the water boundary extraction. Results The research results indicate that (1) among the six models, the CWI model demonstrates the best performance, effectively distinguishing between slope, water, and shadow water, leading to a highly accurate outline of the barrier lake. However, a limitation of this model is the presence of a few mountain shadows in the middle of the slope. (2) The decision tree classification method based on slope achieved an overall accuracy of 89.31% and a kappa coefficient of 0.84. It effectively extracts the actual water range, excluding slope shoreline and mountain shadows, and provides a clearer lake boundary. Nevertheless, black fragments observed in the lower area of the barrier lake, likely due to landslides and mountain shadows, remained challenging to classify. Overall, the decision tree classification-based method proved effective in identifying water bodies, particularly in areas with rugged terrain and numerous shadows. Conclusion This paper proposes a method for extracting water bodies from barrier lakes in high mountain areas using decision tree classification. By incorporating slope information into conventional water body extraction methods, this approach accurately extracts the water boundary, effectively eliminates shadows from steep slopes, retain shadowed water on gentler slopes, and improves extraction efficiently. The simplicity and high extraction efficiency of this method make it a practical solution for widespread application.
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spelling doaj-art-ec250b70767049da86f4a1009abfa5d12025-08-20T02:36:15ZzhoEditorial Department of Bulletin of Geological Science and Technology地质科技通报2096-85232024-11-01436516210.19509/j.cnki.dzkq.tb20240125dzkjtb-43-6-51A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram HighwayYousan LI0Guangchao CAO1Meiliang ZHAO2Wenqian YE3Wanqiang QI4Hongkui YANG5Yuanzhao WU6Qiang GU7Yuguo LU8Shilin WANG9Qinghai Province Key Laboratory of Physical Geography and Environmental Process, College of Geographical Science, Qinghai Normal University, Xining 810008, ChinaQinghai Province Key Laboratory of Physical Geography and Environmental Process, College of Geographical Science, Qinghai Normal University, Xining 810008, ChinaQinghai Province Key Laboratory of Physical Geography and Environmental Process, College of Geographical Science, Qinghai Normal University, Xining 810008, ChinaQinghai Province Key Laboratory of Physical Geography and Environmental Process, College of Geographical Science, Qinghai Normal University, Xining 810008, ChinaXining Natural Resources Comprehensive Survey Center, China Geological Survey, Xining 810000, ChinaQinghai Province Key Laboratory of Physical Geography and Environmental Process, College of Geographical Science, Qinghai Normal University, Xining 810008, ChinaXining Natural Resources Comprehensive Survey Center, China Geological Survey, Xining 810000, ChinaXining Natural Resources Comprehensive Survey Center, China Geological Survey, Xining 810000, ChinaXining Natural Resources Comprehensive Survey Center, China Geological Survey, Xining 810000, ChinaExploitation and Production Research Institute of Northwest Branch of SINOPEC Corporation, Urumqi 830000, ChinaThe water dynamics of barrier lakes in high mountain areas are crucial for risk assessment, disaster prediction, safety management, and decision-making. Objective and Methods To accurately and efficiently extract the water boundaries of mountainous barrier lakes, this paper focuses on the Attabad barrier lake along the Karakoram Highway, proposing a water extraction method based on decision tree classification. This method incorporates slope information into six conventional water extraction methods for decision tree classification. The effectiveness of these six methods was compared for extracting water from barrier lakes in the experimental area. The best-performing methods suitable for barrier lakes in high-altitude areas were applied to extract the water body range of the Attabad barrier lake.Accuracy was assessed using a confusion matrix, and classification post-processing was performed to refine the water boundary extraction. Results The research results indicate that (1) among the six models, the CWI model demonstrates the best performance, effectively distinguishing between slope, water, and shadow water, leading to a highly accurate outline of the barrier lake. However, a limitation of this model is the presence of a few mountain shadows in the middle of the slope. (2) The decision tree classification method based on slope achieved an overall accuracy of 89.31% and a kappa coefficient of 0.84. It effectively extracts the actual water range, excluding slope shoreline and mountain shadows, and provides a clearer lake boundary. Nevertheless, black fragments observed in the lower area of the barrier lake, likely due to landslides and mountain shadows, remained challenging to classify. Overall, the decision tree classification-based method proved effective in identifying water bodies, particularly in areas with rugged terrain and numerous shadows. Conclusion This paper proposes a method for extracting water bodies from barrier lakes in high mountain areas using decision tree classification. By incorporating slope information into conventional water body extraction methods, this approach accurately extracts the water boundary, effectively eliminates shadows from steep slopes, retain shadowed water on gentler slopes, and improves extraction efficiently. The simplicity and high extraction efficiency of this method make it a practical solution for widespread application.https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20240125decision tree classification modelattabad barrier lakewater body indexkarakoram highwaywater extraction mothod
spellingShingle Yousan LI
Guangchao CAO
Meiliang ZHAO
Wenqian YE
Wanqiang QI
Hongkui YANG
Yuanzhao WU
Qiang GU
Yuguo LU
Shilin WANG
A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway
地质科技通报
decision tree classification model
attabad barrier lake
water body index
karakoram highway
water extraction mothod
title A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway
title_full A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway
title_fullStr A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway
title_full_unstemmed A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway
title_short A method for extracting water from barrier lake in high mountain areas based on decision tree classification: A case study of Attabad barrier lake on the Karakoram Highway
title_sort method for extracting water from barrier lake in high mountain areas based on decision tree classification a case study of attabad barrier lake on the karakoram highway
topic decision tree classification model
attabad barrier lake
water body index
karakoram highway
water extraction mothod
url https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20240125
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