Mapping taluses using deep learning and high-resolution satellite images Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1080/17538947.2025.2484466
Taluses are widely distributed in alpine regions such as the Tibetan Plateau. Despite their critical environmental and geohazard roles, taluses have only been mapped in limited regions. This study presents an effective approach to identifying taluses by capturing their morphological features using deep learning (DeepLab V3+ with an attention mechanism) and high-resolution satellite images. The approach was applied to 2-m-resolution GaoFen satellite images to map taluses in the source area of the Yellow River in the eastern Tibetan Plateau and compile the first comprehensive talus records of the region. The results obtained were highly accurate, with 88.6% of the F1 score compared to manual interpretations. The mapped taluses covered approximately 3.89 × 103 km2, 3.19% of the region, with the vast majority located at moderate elevations (4,000–5,000 m asl) and moderate slopes (10–35°). The mapped areas are characterized by frequent freeze – thaw cycles, significant terrain ruggedness, and sparse vegetation cover. The results reveal other interesting characteristics of talus distribution regarding lithology, permafrost thermal stability, and precipitation. These findings could provide valuable information about the forces that drive talus formation and improved understanding of taluses in the Tibetan Plateau and globally by combining recent advances in artificial intelligence and Earth observations.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/17538947.2025.2484466
- OA Status
- gold
- Cited By
- 1
- References
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4409163451Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/17538947.2025.2484466Digital Object Identifier
- Title
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Mapping taluses using deep learning and high-resolution satellite imagesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-02Full publication date if available
- Authors
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Decai Jiang, Min Feng, Dezhao Yan, Yingzheng Wang, Jinhao Xu, Ning Wang, Jianbang Wang, Xinqiao LiList of authors in order
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https://doi.org/10.1080/17538947.2025.2484466Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1080/17538947.2025.2484466Direct OA link when available
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Deep learning, High resolution, Satellite, Remote sensing, Cartography, Geography, Artificial intelligence, Satellite imagery, Computer science, Engineering, Aerospace engineeringTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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