Analysis of Landslide Susceptibility Using Remote Sensing and Geographic Information Systems (GIS)

Thesis Abstract

Abstract
Landslides pose significant threats to communities, infrastructure, and the environment, making their analysis and prediction crucial for risk management and mitigation efforts. This thesis focuses on the analysis of landslide susceptibility using Remote Sensing and Geographic Information Systems (GIS) techniques. The study aims to develop a comprehensive understanding of the factors influencing landslide occurrence and to create a reliable model for predicting landslide susceptibility in a specific study area. The research begins with an introduction that provides background information on landslides, emphasizing the need for accurate susceptibility analysis and the role of remote sensing and GIS technologies in this field. The problem statement highlights the challenges associated with landslide susceptibility assessment, while the objectives of the study outline the specific goals and research questions to be addressed. The limitations and scope of the study define the boundaries and constraints of the research, setting expectations for the outcomes. Chapter two presents a detailed literature review, covering ten key areas related to landslide susceptibility analysis, remote sensing techniques, GIS applications, and relevant case studies. This review serves as a foundation for understanding existing knowledge and identifying gaps that the current research aims to address. Chapter three focuses on the research methodology, detailing the steps involved in data collection, processing, analysis, and model development. The methodology section includes information on the study area, data sources, data preprocessing techniques, statistical methods, and model validation procedures. It also discusses the selection of variables and parameters for the susceptibility model, highlighting the rationale behind each decision. Chapter four presents the findings of the study, including the results of the susceptibility analysis, model performance evaluation, and spatial distribution of landslide susceptibility in the study area. The discussion section interprets the findings, compares them with existing literature, and explores the implications for landslide risk management and mitigation strategies. Finally, chapter five provides a summary of the research findings, conclusions drawn from the study, and recommendations for future research and practical applications. The significance of the study is highlighted, emphasizing its contribution to the field of landslide susceptibility analysis and the potential benefits for stakeholders involved in disaster risk reduction and land use planning. Overall, this thesis contributes to the advancement of knowledge in landslide susceptibility analysis by integrating remote sensing and GIS technologies to create a robust and reliable model for predicting landslide occurrence. The research outcomes have the potential to improve decision-making processes and enhance preparedness and resilience to landslides in vulnerable areas.