Unsupervised machine learning with different sampling strategies and topographic factors for distinguishing between landslide source and runout areas to improve landslide inventory production
This study derived 12 topographical and hydrological factors related to landslides from a 10-m digital elevation model. Three unsupervised machine learning algorithms were employed to distinguish between the features of landslide sources and runout areas for Typhoon Morakot. Two sampling strategies...
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| Principais autores: | , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
Taylor & Francis Group
2024-12-01
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| Serija: | Geomatics, Natural Hazards & Risk |
| Teme: | |
| Online dostop: | https://www.tandfonline.com/doi/10.1080/19475705.2024.2406302 |
| Oznake: |
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