Machine learning approaches for mapping and predicting landslide-prone areas in São Sebastião (Southeast Brazil)

Machine learning approaches for mapping and predicting landslide-prone areas in São Sebastião (Southeast Brazil)

This study employs machine learning techniques to map and predict landslide-prone areas in São Sebastião, Brazil, a region susceptible to landslides due to its steep terrain and intense rainfall. We compared five algorithms: Random Forest, Gradient Boosting, Support Vector Machine, Artificial Neural...

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Bibliographic Details
Main Authors: Enner Alcântara, Cheila Flávia Baião, Yasmim Carvalho Guimarães, José Roberto Mantovani, José Antonio Marengo
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2025-06-01
Series:Natural Hazards Research
Subjects:
Landslide susceptibility
Machine learning
Land use change
São sebastião
Brazil
Online Access:http://www.sciencedirect.com/science/article/pii/S2666592124000751
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http://www.sciencedirect.com/science/article/pii/S2666592124000751

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