2023
DOI: 10.12912/27197050/172569
|View full text |Cite
|
Sign up to set email alerts
|

Landslide Hazard Assessment in the Heterogeneous Geomorphological and Environmental Context of the Rif Region, Morocco – A Machine Learning Approach

Maryem Hamidi,
Tarik Bouramtane,
Shiny Abraham
et al.

Abstract: Landslides are considered to be one of the most significant and critical natural hazards in the heterogeneous geomorphological setting of the Rif region of Morocco. Despite the high susceptibility to landslides, the region lacks detailed studies. Therefore, this research introduces four advanced machine learning methods, namely Support Vector Machine (SVM), Classification and Regression Trees (CART), Multivariate Discriminant Analysis (MDA), and Logistic Regression (LR), to perform landslide susceptibility map… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2025
2025

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 50 publications
0
1
0
Order By: Relevance
“…In Morocco, several studies were carried out using remote sensing. [Adiri et al, 2017;Hamidi et al, 2023] conducted a study with the aim to compare the different remotely sensed data in automatic lineaments extraction such us: ASTER, Landsat 8 and Sentinel. The validation of the different results derived from this work showed that the sentinel 1 are the most efficient data in the restitution of the lineaments.…”
Section: Adapted Methodologymentioning
confidence: 99%
“…In Morocco, several studies were carried out using remote sensing. [Adiri et al, 2017;Hamidi et al, 2023] conducted a study with the aim to compare the different remotely sensed data in automatic lineaments extraction such us: ASTER, Landsat 8 and Sentinel. The validation of the different results derived from this work showed that the sentinel 1 are the most efficient data in the restitution of the lineaments.…”
Section: Adapted Methodologymentioning
confidence: 99%