Analysis of Landslide Susceptibility Using Remote Sensing and Geographic Information Systems (GIS) Techniques in a Selected Region

Thesis Abstract

Abstract
This thesis presents a comprehensive analysis of landslide susceptibility in a selected region using advanced remote sensing and Geographic Information Systems (GIS) techniques. Landslides are a significant geological hazard that poses threats to lives, properties, and infrastructure in many regions globally. Understanding and predicting landslide susceptibility are crucial for effective risk management and mitigation strategies. Remote sensing and GIS technologies offer powerful tools for assessing and mapping landslide susceptibility by integrating various spatial data layers and analytical techniques. The research begins with an introduction to the study, providing background information on landslides and the importance of assessing susceptibility in the selected region. The problem statement highlights the need for accurate landslide susceptibility mapping to inform decision-making processes and mitigate potential risks. The objectives of the study are outlined to establish a clear direction for the research, focusing on the application of remote sensing and GIS techniques to analyze landslide susceptibility factors. Limitations and scope of the study are discussed to define the boundaries and constraints of the research, ensuring a realistic and achievable outcome. The significance of the study emphasizes the potential impact of the findings on disaster preparedness, land use planning, and infrastructure development in the study area. The structure of the thesis provides an overview of the organization and flow of the research, guiding readers through the subsequent chapters. Chapter two comprises a comprehensive literature review that examines existing studies and methodologies related to landslide susceptibility assessment, remote sensing, GIS applications, and spatial analysis techniques. The review synthesizes relevant information to build a strong theoretical foundation for the research and identify gaps for further investigation. Chapter three details the research methodology, outlining the data collection process, selection of landslide susceptibility factors, remote sensing data acquisition, GIS analysis techniques, and model development. The chapter also discusses the validation and accuracy assessment of the landslide susceptibility model to ensure robust and reliable results. Chapter four presents a detailed discussion of the findings, including the spatial distribution of landslide susceptibility zones, the influence of various factors on susceptibility, and the effectiveness of the developed model. The results are analyzed, interpreted, and compared with existing studies to provide insights into the factors contributing to landslide susceptibility in the study area. In chapter five, the conclusion summarizes the key findings of the research, highlighting the implications for landslide risk management and future research directions. The summary underscores the importance of remote sensing and GIS techniques in assessing landslide susceptibility and emphasizes the need for proactive measures to mitigate landslide hazards in the selected region. Overall, this thesis contributes to the field of geology by demonstrating the effectiveness of remote sensing and GIS technologies in analyzing landslide susceptibility and providing valuable insights for disaster management authorities, urban planners, and policymakers. The findings offer practical implications for enhancing landslide risk assessment and mitigation strategies, emphasizing the importance of integrating spatial technologies in geohazard studies for sustainable development and disaster resilience.