Enhancing landslide susceptibility predictions with XGBoost and SHAP: a data-driven explainable AI method
Landslide susceptibility mapping is essential for disaster risk management, especially in geologically sensitive regions like the Himalayas, where steep slopes, heavy rainfall, and human activities intensify risks. This study integrates eXtreme Gradient Boosting (XGBoost) with SHapley Additive exPla...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2514725 |
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