Thesis Abstract

Abstract
Landslides pose a significant threat to communities and infrastructure worldwide, making their accurate prediction and analysis crucial for disaster risk reduction and management. This thesis focuses on the analysis of landslide susceptibility using remote sensing and Geographic Information System (GIS) techniques. The study aims to develop a comprehensive understanding of the factors contributing to landslide susceptibility in a specific region, with the ultimate goal of creating accurate landslide susceptibility maps to aid in mitigation and preparedness efforts. The research begins with an introduction that provides background information on landslides, highlighting the importance of studying landslide susceptibility for disaster risk reduction. The problem statement emphasizes the need for accurate and reliable methods for assessing landslide susceptibility, while the objectives of the study outline the specific goals and aims of the research. The limitations and scope of the study are also discussed, along with the significance of the research in contributing to the field of geoscience. Chapter two presents a thorough literature review, examining existing studies on landslide susceptibility assessment, remote sensing techniques, GIS applications, and relevant methodologies. The review synthesizes key findings and identifies gaps in the current literature that the present study seeks to address. Chapter three outlines the research methodology, detailing the data collection process, variables considered, and the analytical techniques employed. The chapter discusses the selection of study area, data sources, and the methods used for processing and analyzing remote sensing and GIS data to assess landslide susceptibility. Chapter four presents a detailed discussion of the findings, including the identification of key factors influencing landslide susceptibility, the development of susceptibility models, and the creation of landslide susceptibility maps. The chapter also discusses the validation of the models and maps, highlighting their accuracy and reliability in predicting landslide susceptibility. Finally, chapter five provides a comprehensive conclusion and summary of the thesis, summarizing the key findings, implications, and recommendations for future research. The study concludes by emphasizing the importance of utilizing remote sensing and GIS techniques for landslide susceptibility analysis and highlights the potential impact of the research on disaster risk reduction and management efforts. Overall, this thesis contributes to the growing body of knowledge on landslide susceptibility analysis and demonstrates the effectiveness of remote sensing and GIS techniques in predicting and mapping landslide-prone areas. The findings of this research have significant implications for land use planning, infrastructure development, and disaster risk management, highlighting the importance of proactive measures to mitigate the impact of landslides on vulnerable communities.

Thesis Overview