Assessment of Ground Instabilities’ Causative Factors Using Multivariate Statistical Analysis Methods: Case of the Coastal Region of Northwestern Rif, Morocco

An assessment of ground instabilities’ causative factors remains a topical subject. Such studies are rare, and evaluation techniques are still under development. The choice of evaluation technique should take into account the materials available and the objective sought. Statistical analysis methods...

Full description

Saved in:
Bibliographic Details
Published in:Geosciences (Basel) 2022-10, Vol.12 (10), p.383
Main Authors: Tribak, Haytam, Gasc-Barbier, Muriel, El Garouani, Abdelkader
Format: Article
Language:English
Subjects:
Analysis
Applied geology
causative factors assessment
Civil Engineering
Coastal zone
Discriminant analysis
Earth science
Earth Sciences
Engineering Sciences
Evaluation
ground instabilities
Hydrology
Instability
Landslides
Landslides & mudslides
Lithology
Mathematical statistics
MCA
Multivariate analysis
multivariate statistic
Multivariate statistical analysis
northwestern Rif
PCA
Principal components analysis
Risques
Rock falls
Rockfall
Sciences of the Universe
Stability
Statistical analysis
Statistical methods
Statistics
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An assessment of ground instabilities’ causative factors remains a topical subject. Such studies are rare, and evaluation techniques are still under development. The choice of evaluation technique should take into account the materials available and the objective sought. Statistical analysis methods are the most widely used, with multivariate analysis being the most accurate. The present work evaluates the weights of the influences of the different factors of ground instability of the coastal region between Tetouan and Jebha through multiple correspondence analysis (MCA) and principal component analysis (PCA). The application of both methods requires an accurate ground instability inventory with study sites that are well documented through modalities of causative factors and other descriptive data. The performed MCA shows that lithology has a significant influence on the type of existing instability. It also helped classify the instabilities into five distinct classes according to their modalities and specify the factors that differentiate the classes. The PCA shows that lithology is the most influential factor in landslides, contrary to rockfalls, where a variety of factors can be preponderant.
ISSN:2076-3263
2076-3263
DOI:10.3390/geosciences12100383