Assessment of Landslide Susceptibility Using GIS and Remote Sensing Techniques in a Mountainous Region

Thesis Abstract

Abstract
Landslides represent a significant natural hazard in mountainous regions, leading to severe consequences on the environment, infrastructure, and human lives. Effective landslide susceptibility assessment is crucial for risk management and mitigation strategies. This study focuses on the assessment of landslide susceptibility using Geographic Information System (GIS) and Remote Sensing techniques in a mountainous region. The research aims to develop a comprehensive understanding of the factors influencing landslide occurrence and to create a reliable susceptibility model for the study area. The first chapter provides an introduction to the research topic, presenting the background, problem statement, objectives, limitations, scope, significance, and structure of the thesis. The subsequent chapter comprises a detailed literature review, covering ten key areas related to landslide susceptibility assessment, GIS, Remote Sensing, and previous studies on similar topics. Chapter three outlines the research methodology, including data collection methods, study area selection criteria, GIS and Remote Sensing techniques employed, landslide inventory preparation, and susceptibility model development. The methodology section also includes a discussion on the validation of the susceptibility model and the assessment of model accuracy. In chapter four, the findings of the study are comprehensively discussed. This section presents the results of the landslide susceptibility assessment, highlighting the key factors contributing to landslide occurrence in the mountainous region. The discussion also includes the comparison of different susceptibility models and the identification of areas with high susceptibility to landslides. The concluding chapter summarizes the key findings of the research and provides insights into the implications of the study results. Recommendations for future research and practical applications of the susceptibility model in landslide risk management are also discussed. Overall, this thesis contributes to the existing body of knowledge on landslide susceptibility assessment and provides valuable insights for stakeholders involved in disaster risk reduction and land use planning in mountainous regions.