Mapping taluses using deep learning and high-resolution satellite images
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 d...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2484466 |
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| author | Decai Jiang Min Feng Dezhao Yan Yingzheng Wang Jinhao Xu Ning Wang Jianbang Wang Xin Li |
| author_facet | Decai Jiang Min Feng Dezhao Yan Yingzheng Wang Jinhao Xu Ning Wang Jianbang Wang Xin Li |
| author_sort | Decai Jiang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-0c2b47b014554c61862ca174011509fb |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-0c2b47b014554c61862ca174011509fb2025-08-25T11:31:48ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2484466Mapping taluses using deep learning and high-resolution satellite imagesDecai Jiang0Min Feng1Dezhao Yan2Yingzheng Wang3Jinhao Xu4Ning Wang5Jianbang Wang6Xin Li7Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, People’s Republic of ChinaUniversity of Chinese Academy of Sciences, Beijing, People’s Republic of ChinaUniversity of Chinese Academy of Sciences, Beijing, People’s Republic of ChinaNational Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaNational Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaChina Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, People’s Republic of ChinaNational Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaUniversity of Chinese Academy of Sciences, Beijing, People’s Republic of ChinaTaluses 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.https://www.tandfonline.com/doi/10.1080/17538947.2025.2484466Talusdeep learningsatellite imagesTibetan Plateau |
| spellingShingle | Decai Jiang Min Feng Dezhao Yan Yingzheng Wang Jinhao Xu Ning Wang Jianbang Wang Xin Li Mapping taluses using deep learning and high-resolution satellite images International Journal of Digital Earth Talus deep learning satellite images Tibetan Plateau |
| title | Mapping taluses using deep learning and high-resolution satellite images |
| title_full | Mapping taluses using deep learning and high-resolution satellite images |
| title_fullStr | Mapping taluses using deep learning and high-resolution satellite images |
| title_full_unstemmed | Mapping taluses using deep learning and high-resolution satellite images |
| title_short | Mapping taluses using deep learning and high-resolution satellite images |
| title_sort | mapping taluses using deep learning and high resolution satellite images |
| topic | Talus deep learning satellite images Tibetan Plateau |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2025.2484466 |
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