Analysis of Landslide Susceptibility in a Mountainous Region Using GIS Techniques

Thesis Abstract

Abstract
Landslides are one of the most significant natural hazards, causing extensive damage to property and posing risks to human lives in mountainous regions. This research focuses on analyzing landslide susceptibility in a specific mountainous region using Geographic Information System (GIS) techniques. The study aims to develop a comprehensive understanding of the factors influencing landslide occurrence and to create a reliable landslide susceptibility map for the target area. The research begins with an introduction to the problem of landslides in mountainous regions, highlighting their impacts and the importance of effective mitigation strategies. The background of the study provides a detailed overview of previous research on landslide susceptibility mapping and the role of GIS in analyzing spatial data for landslide risk assessment. The problem statement identifies the need for a detailed investigation into landslide susceptibility in the specific mountainous region under study. The objectives of the study include identifying the key factors contributing to landslide susceptibility, developing a GIS-based model for landslide susceptibility mapping, and assessing the accuracy of the model through validation processes. The limitations of the study are acknowledged, including data availability constraints and the inherent uncertainties associated with landslide prediction models. The scope of the study is defined in terms of the geographical extent, data sources, and methodology used in the analysis. The significance of the study lies in its potential to provide valuable insights for land use planning, disaster risk reduction, and emergency response strategies in mountainous regions prone to landslides. The structure of the thesis outlines the organization of the research into distinct chapters, from the introduction to the conclusion, ensuring a systematic presentation of the findings. In the literature review, ten key themes related to landslide susceptibility analysis, GIS applications in landslide studies, and relevant methodologies are discussed. The review of existing literature provides a theoretical foundation for the research, highlighting gaps in current knowledge and guiding the selection of appropriate methods for data analysis. The research methodology section describes the data collection process, including the acquisition of topographic, geological, rainfall, and land cover data for the study area. Eight specific steps are outlined, including data preprocessing, spatial analysis, and model validation procedures. The chapter emphasizes the use of GIS tools and techniques for processing spatial data and generating landslide susceptibility maps. In the discussion of findings chapter, the results of the GIS analysis are presented, including the identification of landslide susceptibility factors, the development of a susceptibility model, and the evaluation of model accuracy. The findings are interpreted in the context of existing literature, highlighting the significance of the research outcomes for landslide risk assessment and management. Finally, the conclusion and summary chapter provide a comprehensive overview of the research findings, reiterating the key contributions of the study and discussing implications for future research and practical applications. The conclusion emphasizes the importance of integrating GIS technologies with traditional methods for landslide susceptibility mapping and highlights the potential for enhancing landslide risk assessment in mountainous regions. In conclusion, this thesis contributes to the field of landslide susceptibility analysis by providing a detailed investigation into the factors influencing landslide occurrence in a mountainous region using GIS techniques. The research outcomes have implications for land use planning, disaster risk reduction, and emergency response strategies, offering valuable insights for mitigating the impacts of landslides in vulnerable areas.