Machine learning and SHAP-based susceptibility assessment of storm flood in rapidly urbanizing areas: a case study of Shenzhen, China
In recent years, urban flooding disasters have occurred frequently. Conducting research on flood susceptibility assessment is critical for urban flood prevention and urban renewal planning. However, determining how to effectively improve the accuracy of flood susceptibility assessment remains a chal...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2024.2311889 |
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