Machine learning methods for landslide mapping studies: A comparative study of SVM and RF algorithms in the Oued Aoulai watershed (Morocco)

Machine learning methods for landslide mapping studies: A comparative study of SVM and RF algorithms in the Oued Aoulai watershed (Morocco)

Effective management of watershed risks and landslides necessitates comprehensive landslide susceptibility mapping. Support vector machine (SVM) and random forest (RF) machine learning models were used to map the landslide susceptibility in Morocco’s Taounate Province. Detailed landslide inventory m...

Full description

Saved in:
Bibliographic Details
Main Authors: Ladel Latifa, Mastere Mohamed, Kader Shuraik, Spalević Velibor, Dudic Branislav
Format: Article
Language:English
Published: De Gruyter 2025-03-01
Series:Open Geosciences
Subjects:
management
landslide susceptibility
machine learning models
factor correlation analysis
area under the curve
morocco
Online Access:https://doi.org/10.1515/geo-2022-0740
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1515/geo-2022-0740

Similar Items