Thesis Abstract

Abstract
Landslides are natural hazards that pose significant threats to communities and infrastructure in various regions worldwide. Understanding the factors contributing to landslide susceptibility is crucial for effective risk assessment and mitigation strategies. This thesis presents a comprehensive analysis of landslide susceptibility using remote sensing and Geographic Information Systems (GIS) in a specific region. The study area, located in [specific region], has experienced recurrent landslide events, making it an ideal case study for investigating landslide susceptibility. The research begins with an introduction (Chapter 1) that provides background information on landslides, highlights the problem statement, outlines the objectives of the study, discusses the limitations and scope of the research, emphasizes the significance of the study, and presents the structure of the thesis. Chapter 2 presents a detailed literature review covering ten key areas related to landslide susceptibility, remote sensing, GIS applications, and relevant methodologies. Chapter 3 focuses on the research methodology, detailing the data collection process, remote sensing techniques employed, GIS analysis methods, and validation procedures. The methodology section also discusses the selection criteria for landslide susceptibility factors, data preprocessing steps, and the development of a susceptibility model using remote sensing data and GIS tools. In Chapter 4, the findings of the study are extensively discussed, including the identification of landslide susceptibility factors, the creation of a susceptibility map, and the evaluation of model performance. The results highlight the significance of factors such as slope gradient, land cover, rainfall intensity, and lithology in determining landslide susceptibility in the study area. The discussion also addresses the strengths and limitations of the susceptibility model developed and provides insights into the practical implications for landslide risk management. Finally, Chapter 5 presents the conclusion and summary of the thesis, summarizing the key findings, discussing the implications for future research, and providing recommendations for enhancing landslide susceptibility mapping using remote sensing and GIS technologies. The research contributes to the existing knowledge on landslide susceptibility assessment and demonstrates the effectiveness of integrating remote sensing and GIS for spatial analysis in landslide-prone regions. In conclusion, this thesis offers valuable insights into the analysis of landslide susceptibility using remote sensing and GIS techniques, providing a foundation for improved landslide risk assessment and management strategies in the specific region and beyond. The findings of this research can inform decision-makers, policymakers, and stakeholders in developing proactive measures to mitigate landslide hazards and enhance community resilience in vulnerable areas. Keywords Landslide susceptibility, Remote sensing, Geographic Information Systems, Spatial analysis, Risk assessment, Hazard mapping, GIS modeling, Landslide mitigation.

Thesis Overview

The project titled "Analysis of Landslide Susceptibility Using Remote Sensing and Geographic Information Systems in a Specific Region" aims to investigate the factors contributing to landslide occurrences in a particular region using advanced technologies such as remote sensing and geographic information systems (GIS). Landslides are a recurring natural hazard that poses significant risks to human lives, infrastructure, and the environment. By conducting a comprehensive analysis of landslide susceptibility in the selected region, this research seeks to enhance understanding of the underlying causes and potential triggers of landslides. Remote sensing techniques, including satellite imagery and aerial photography, will be utilized to gather data on the terrain, land cover, and other relevant environmental variables. This data will be integrated into GIS software to create detailed spatial models for assessing landslide susceptibility. By combining remote sensing data with geographic information systems, the research aims to develop accurate predictive models that can identify areas prone to landslides based on various factors such as slope gradient, soil type, land use, and precipitation patterns. The research overview will also explore the methodology employed in collecting and analyzing data, including the selection of study sites, data acquisition processes, and the application of statistical techniques to develop landslide susceptibility models. Additionally, the study will discuss the significance of the research findings in terms of improving landslide risk management strategies and informing land use planning and development policies in the region. Overall, this research project seeks to contribute valuable insights into understanding landslide susceptibility using cutting-edge technologies, with the ultimate goal of enhancing disaster preparedness and resilience in the specific region under investigation.