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.

Thesis Overview

The project titled "Analysis of Landslide Susceptibility Using Remote Sensing and Geographic Information Systems (GIS)" aims to investigate the factors contributing to landslide susceptibility in a specific geographic area using advanced technologies such as remote sensing and GIS. Landslides are natural hazards that can result in significant damage to infrastructure, loss of life, and environmental degradation. Understanding the factors that influence landslide susceptibility is crucial for effective risk assessment, mitigation strategies, and disaster management. The research will begin with an introduction providing background information on landslides, their impact, and the importance of studying landslide susceptibility. The problem statement will highlight the need for a comprehensive analysis of landslide susceptibility in the study area. The objectives of the study will outline the specific goals to be achieved, such as identifying high-risk areas and assessing the contributing factors. Limitations of the study will be acknowledged, including constraints such as data availability, time, and resources. The scope of the study will define the geographical area, types of landslides considered, and the methodology employed. The significance of the study will be emphasized, highlighting the potential impact on disaster risk reduction, urban planning, and environmental conservation. The research methodology will involve a detailed literature review to explore existing knowledge on landslide susceptibility, remote sensing techniques, and GIS applications. Data collection methods will include satellite imagery analysis, field surveys, and geospatial data processing. Statistical analysis and modeling techniques will be utilized to assess landslide susceptibility factors and develop predictive maps. The findings chapter will present the results of the analysis, including maps depicting landslide susceptibility zones, identified risk factors, and spatial patterns. The discussion will interpret the findings, evaluate the accuracy of the predictive models, and compare results with existing studies. Implications for land use planning, disaster preparedness, and environmental management will be discussed. In conclusion, the project will summarize the key findings, implications, and recommendations for future research and practical applications. The research outcomes are expected to contribute to the understanding of landslide susceptibility dynamics and provide valuable insights for decision-makers, planners, and stakeholders involved in disaster risk management and land use planning.