Landslide Susceptibility Assessment Using Statistical Multivariate Analysis “PCA” in the Mediterranean Kabylia

Résumé

Abstract Landslides are one of the most catastrophic geo-risks observed in northern Algeria, particularly in the regions of mountain ranges (Mediterranean Kabylia), where the processes are spectacular. Over the past decade, the landslides risk has become increasingly amplified in urban space, mainly affecting the economy and human life. This highlights the importance and the need to predict the spatial occurrence of these events in the national territory. In order to better manage this phenomenon, decision-makers must be able to have susceptibility maps, allowing them to identify areas in their region where new landslides will have a higher probability of being triggered in the future and of predefine the damage associated with this phenomenon. However, approaches to assessing landslide sensitivity require a good knowledge of previously observed scenarios and include data collection and management, as well as spatial and statistical analyzes. In this study, a new multivariate statistical approach "PCA" was proposed to produce landslide susceptibility maps of the study area in a GIS system. This study allows the automatic analysis of most of the parameters related to the occurrence of slope failures while reducing the factors not influencing the triggering of landslides, this eliminates the effect of redundancy between the factors studied.

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