Evaluating Factors Affecting Flood Susceptibility in the Yangtze River Delta Using Machine Learning Methods

Evaluating Factors Affecting Flood Susceptibility in the Yangtze River Delta Using Machine Learning Methods

Abstract Floods are widespread and dangerous natural hazards worldwide. It is essential to grasp the causes of floods to mitigate their severe effects on people and society. The key drivers of flood susceptibility in rapidly urbanizing areas can vary depending on the specific context and require fur...

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Bibliographic Details
Main Authors: Kaili Zhu, Zhaoli Wang, Chengguang Lai, Shanshan Li, Zhaoyang Zeng, Xiaohong Chen
Format: Article
Language:English
Published: SpringerOpen 2024-10-01
Series:International Journal of Disaster Risk Science
Subjects:
Climate change
Flood susceptibility
Human activity
Machine learning methods
Yangtze River Delta core urban agglomeration
Online Access:https://doi.org/10.1007/s13753-024-00590-6
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https://doi.org/10.1007/s13753-024-00590-6

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