Thesis Abstract

**Abstract
** Landslides are natural hazards that pose significant risks to communities living in mountainous regions. The ability to assess landslide susceptibility is crucial for risk mitigation and disaster management. Geographic Information Systems (GIS) have proven to be valuable tools in analyzing and mapping landslide susceptibility by incorporating various spatial data layers. This thesis focuses on the assessment of landslide susceptibility using GIS in a mountainous region. The study begins with an introduction that provides an overview of the research problem and the significance of the study. It delves into the background of the study, highlighting the importance of understanding landslide susceptibility in mountainous regions. The problem statement identifies the gap in current research and emphasizes the need for a comprehensive GIS-based approach to assess landslide susceptibility. The objectives of the study outline the specific goals and research questions that will be addressed. The limitations and scope of the study provide a clear understanding of the boundaries and constraints within which the research will be conducted. The significance of the study emphasizes the potential impact of the research on landslide risk management and community resilience. Lastly, the structure of the thesis gives an overview of how the research is organized into different chapters. The literature review in Chapter Two provides a detailed analysis of existing studies on landslide susceptibility assessment, GIS applications in landslide studies, and methodologies for evaluating landslide susceptibility factors. It explores various factors influencing landslide susceptibility, such as topography, geology, land cover, and hydrology, and discusses the importance of integrating these factors within a GIS framework. Chapter Three outlines the research methodology employed in this study. It includes details on data collection methods, GIS techniques used for data processing and analysis, landslide susceptibility modeling algorithms, and validation procedures. The chapter also discusses the selection criteria for the study area and the rationale behind choosing specific landslide susceptibility factors for analysis. In Chapter Four, the findings of the study are presented and discussed in detail. The results of the landslide susceptibility modeling using GIS are analyzed, and the spatial distribution of landslide susceptibility zones in the mountainous region is mapped. The discussion focuses on the significance of different factors in influencing landslide susceptibility and highlights the implications of the findings for landslide risk assessment and management. Finally, Chapter Five presents the conclusions drawn from the study and provides a summary of the key findings and implications. The study contributes to the understanding of landslide susceptibility in mountainous regions and demonstrates the effectiveness of GIS in assessing and mapping landslide risk. Recommendations for future research and practical implications for disaster management authorities are also discussed. In conclusion, this thesis contributes to the field of landslide susceptibility assessment by integrating GIS technology with traditional landslide analysis methods. The research findings provide valuable insights for policymakers, planners, and stakeholders involved in landslide risk mitigation and disaster preparedness in mountainous regions.

Thesis Overview