A Comprehensive Review On Landslide Susceptibility Zonation Techniques

Singh Kanwarpreet (), Bhardwaj Vanshika, Sharma Abhishek and Thakur Shalini
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Singh Kanwarpreet: Civil Engineering Department, Chandigarh University, Mohali, India
Bhardwaj Vanshika: Civil Engineering Department, Chandigarh University, Mohali, India
Sharma Abhishek: Civil Engineering Department, Chandigarh University, Mohali, India
Thakur Shalini: Civil Engineering Department, Chandigarh University, Mohali, India

Quaestiones Geographicae, 2024, vol. 43, issue 1, 79-91

Abstract: This review paper provides an overview of recent research on landslide susceptibility. Landslides are a natural phenomenon that can cause significant damage to infrastructure and endanger human lives. The paper presents an in-depth analysis of the factors that contribute to landslide susceptibility, including geological, hydrological and anthropogenic factors. It also discusses various methods and techniques used to assess landslide susceptibility, including statistical models, geographic information systems (GIS) and remote sensing. The paper examines the advantages and limitations of these methods and highlights the need for an integrated approach that combines multiple techniques to improve accuracy and reliability. Additionally, the paper discusses the challenges associated with developing landslide susceptibility maps and emphasises the importance of considering uncertainties and risk assessments. The review paper concludes by identifying the gaps in current research and suggesting potential directions for future studies. Overall, this review paper provides a comprehensive analysis of landslide susceptibility, which can serve as a valuable resource for researchers, practitioners and policymakers working in this field.

Keywords: natural hazards; landslides; landslide susceptibility zonation techniques; ensembled approach (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:quageo:v:43:y:2024:i:1:p:79-91:n:1005

DOI: 10.14746/quageo-2024-0005

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