Unveiling Urban Flood Vulnerability: A Machine Learning Approach for Mapping High Risk Zones in Tetouan City, Northern Morocco

Unveiling Urban Flood Vulnerability: A Machine Learning Approach for Mapping High Risk Zones in Tetouan City, Northern Morocco

This study examines urban flood vulnerability in Tetouan city, Northern Morocco, using four machine learning models—Classification and Regression Tree (CART), Support Vector Machine (SVM), Logistic Regression (LR), and Factorial Discriminant Analysis (FDA)—to identify and map flood-prone areas. The...

Full description

Saved in:
Bibliographic Details
Main Authors: Oussama Mekkaoui, Moad Morarech, Tarik Bouramtane, Laurent Barbiero, Maryem Hamidi, Hamza Akka, Rania Prya Muthusamy Rengasamy
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Urban Science
Subjects:
flood vulnerability
machine learning models
urban planning
risk management
Tetouan
Online Access:https://www.mdpi.com/2413-8851/9/3/70
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2413-8851/9/3/70

Similar Items