Thesis Abstract

**Abstract
** Landslides are a widespread natural hazard that poses significant risks to human life, infrastructure, and the environment. This study focuses on investigating landslide susceptibility in a specific region through the integration of Geographic Information System (GIS) and remote sensing techniques. The utilization of GIS and remote sensing technologies allows for the identification and analysis of factors contributing to landslide susceptibility, providing valuable insights for risk assessment and management strategies. The research begins by introducing the background of the study, highlighting the importance of understanding landslide susceptibility for effective mitigation measures. The problem statement underscores the need to address the increasing frequency and impact of landslides in the study area. The objectives of the study are outlined to guide the research process, aiming to assess the spatial distribution of landslide susceptibility factors and develop a susceptibility map for the region. Limitations of the study are acknowledged, recognizing constraints such as data availability, accuracy, and scale limitations that may impact the research outcomes. The scope of the study is defined to focus on a specific region, utilizing GIS and remote sensing techniques to analyze topographic, geological, and environmental factors influencing landslide susceptibility. The significance of the study lies in its potential to enhance landslide risk management strategies and improve disaster preparedness in the region. The structure of the thesis is articulated, outlining the organization of chapters to provide a clear framework for the research. Chapter One introduces the research context, objectives, and methodology, setting the foundation for the subsequent chapters. Chapter Two presents a comprehensive literature review on landslide susceptibility assessment, highlighting key concepts, methods, and case studies relevant to the study. Chapter Three details the research methodology, including data collection, processing techniques, and modeling approaches employed to assess landslide susceptibility. Various aspects such as data sources, software tools, and analytical methods are described to elucidate the research process. Chapter Four presents a detailed discussion of the findings, interpreting the results of the susceptibility analysis and discussing the implications for landslide risk management. Finally, Chapter Five summarizes the research findings, conclusions, and recommendations derived from the study. The conclusion highlights the key insights gained from the research and their implications for future studies and practical applications in landslide risk assessment. Overall, this thesis contributes to the advancement of understanding landslide susceptibility through the application of GIS and remote sensing techniques, providing valuable insights for effective risk management practices in the study region.

Thesis Overview