Thesis Abstract

Abstract
Landslides are natural disasters that pose significant threats to human lives, infrastructure, and the environment. The use of remote sensing and Geographic Information System (GIS) techniques has become increasingly important in understanding and assessing landslide susceptibility. This thesis focuses on the analysis of landslide susceptibility using remote sensing and GIS techniques in a selected region. The study area was chosen based on its susceptibility to landslides and the availability of relevant data. The research begins with an introduction outlining the importance of studying landslide susceptibility and the need for advanced techniques like remote sensing and GIS. The background of the study provides a comprehensive overview of previous research on landslides, remote sensing, and GIS applications in landslide analysis. The problem statement identifies the gaps in existing research and highlights the need for a detailed investigation into landslide susceptibility in the selected region. The objectives of the study include mapping landslide susceptibility zones, identifying key factors contributing to landslides, and assessing the effectiveness of remote sensing and GIS techniques in landslide analysis. The limitations of the study are also discussed, including data availability, accuracy, and potential biases. The scope of the study outlines the geographic extent, timeframe, and specific methodologies to be employed. The significance of the study lies in its potential to improve landslide risk assessment and mitigation strategies in the selected region. By understanding the spatial distribution of landslide susceptibility factors, decision-makers can implement proactive measures to reduce the impact of landslides on communities and infrastructure. The structure of the thesis provides a roadmap for the reader, outlining the chapters and sub-sections that will be covered in detail. In the literature review, ten key themes related to landslides, remote sensing, GIS, and susceptibility mapping are discussed. These themes provide a theoretical foundation for the research and highlight current trends and methodologies in landslide analysis. The research methodology section outlines the data sources, analysis techniques, and modeling approaches used to map landslide susceptibility in the study area. The findings of the study are presented in Chapter Four, where the results of the susceptibility mapping are discussed in detail. Spatial patterns of landslide susceptibility factors are analyzed, and the effectiveness of remote sensing and GIS techniques in identifying high-risk areas is evaluated. The discussion highlights the implications of the findings for landslide risk management and urban planning in the region. In the conclusion and summary chapter, the key findings of the study are summarized, and recommendations for future research and policy implications are provided. The thesis contributes to the growing body of knowledge on landslide susceptibility analysis and demonstrates the value of remote sensing and GIS techniques in enhancing our understanding of landslide hazards. Overall, this thesis provides valuable insights into the application of remote sensing and GIS for landslide susceptibility analysis and offers practical recommendations for improving landslide risk management in the selected region. By integrating advanced technologies with traditional geological methods, this research contributes to the broader goal of enhancing disaster preparedness and resilience in landslide-prone areas.

Thesis Overview