Assessing Flood and Landslide Susceptibility Using XGBoost: Case Study of the Basento River in Southern Italy

Assessing Flood and Landslide Susceptibility Using XGBoost: Case Study of the Basento River in Southern Italy

Floods and landslides are two distinct natural phenomena influenced by different conditioning factors, though some environmental triggers may overlap. This study applied eXtreme Gradient Boosting (XGBoost) to develop susceptibility maps for both phenomena, using a unified approach based on the same...

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Bibliographic Details
Main Authors: Marica Rondinone, Silvano Fortunato Dal Sasso, Htay Htay Aung, Lucia Contillo, Giusy Dimola, Marcello Schiattarella, Mauro Fiorentino, Vito Telesca
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
XGBoost
multi-hazard mapping
flood susceptibility
landslide susceptibility
machine learning
remote sensing
Online Access:https://www.mdpi.com/2076-3417/15/10/5290
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