Evaluation of Conditioning Factors of Slope Instability and Continuous Change Maps in the Generation of Landslide Inventory Maps Using Machine Learning (ML) Algorithms

Evaluation of Conditioning Factors of Slope Instability and Continuous Change Maps in the Generation of Landslide Inventory Maps Using Machine Learning (ML) Algorithms

Landslides are recognized as high-impact natural hazards in different regions around the world; therefore, they are extensively researched by experts. Landslide inventories are essential to identify areas that are likely to be affected in the future, thereby enabling interventions to prevent loss of...

Full description

Saved in:
Bibliographic Details
Main Authors: Rocío N. Ramos-Bernal, René Vázquez-Jiménez, Claudia A. Cantú-Ramírez, Antonio Alarcón-Paredes, Gustavo A. Alonso-Silverio, Adrián G. Bruzón, Fátima Arrogante-Funes, Fidel Martín-González, Carlos J. Novillo, Patricia Arrogante-Funes
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
landslides
continuous change maps
conditioning factors
machine learning
Science
Q
Online Access:https://doaj.org/article/f1611f2935aa421bb25b372fc4a90ee7
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items