Thesis Abstract

Abstract
Landslides pose significant risks to communities residing in mountainous regions, necessitating advanced techniques for susceptibility analysis to mitigate potential disasters. This thesis investigates the application of Remote Sensing and Geographic Information System (GIS) technologies to analyze landslide susceptibility in a mountainous region. The study area selected for this research is characterized by complex terrain and historical landslide occurrences, making it an ideal location for such analysis. The introductory chapter provides a comprehensive overview of the research, including the background of the study, problem statement, objectives, limitations, scope, significance, and the structure of the thesis. The subsequent literature review chapter synthesizes existing knowledge on landslides, susceptibility analysis methods, Remote Sensing, and GIS techniques, highlighting their relevance to the study. The methodology chapter outlines the research design, data collection, and analysis procedures involved in the investigation. Specific contents include data acquisition, preprocessing, terrain analysis, selection of landslide conditioning factors, and model development using Remote Sensing and GIS tools. Various statistical and spatial analysis techniques are employed to assess landslide susceptibility accurately. The findings chapter presents a detailed discussion of the results obtained from the susceptibility analysis. It includes the identification of high-risk zones, validation of the model, and the assessment of model performance. The spatial distribution of landslide susceptibility in the study area is analyzed, providing valuable insights for land-use planning and disaster management strategies. In the concluding chapter, the implications of the research findings are discussed, emphasizing the importance of using advanced technologies for landslide susceptibility assessment. The significance of the study lies in its contribution to improving landslide risk assessment and preparedness in mountainous regions. Recommendations for future research and practical applications of the findings are also provided. Overall, this thesis contributes to the existing body of knowledge on landslide susceptibility analysis by demonstrating the effectiveness of Remote Sensing and GIS techniques in assessing landslide hazards in mountainous regions. The results of this study have practical implications for disaster management authorities, urban planners, and policymakers to enhance preparedness and mitigate the impacts of landslides on vulnerable communities.

Thesis Overview

The project titled "Analysis of Landslide Susceptibility Using Remote Sensing and GIS Techniques in a Mountainous Region" aims to investigate and analyze the factors contributing to landslide susceptibility in a mountainous region utilizing advanced remote sensing and Geographic Information System (GIS) technologies. This research overview provides a detailed explanation of the project methodology, objectives, significance, and expected outcomes. Landslides are a significant natural hazard in mountainous regions, posing risks to infrastructure, communities, and the environment. Understanding the factors influencing landslide susceptibility is crucial for effective hazard mitigation and land-use planning. Remote sensing and GIS technologies offer valuable tools for mapping, analyzing, and predicting landslide susceptibility by integrating spatial data on terrain characteristics, land cover, geology, and environmental factors. The primary objective of this research is to assess landslide susceptibility in a specific mountainous region by applying remote sensing and GIS techniques. The study will involve collecting satellite imagery, digital elevation models, land cover data, and geological maps to create a comprehensive spatial database. Various data processing and analysis methods, such as image classification, terrain modeling, and spatial overlay, will be employed to identify potential landslide-prone areas based on known triggers and historical events. The significance of this research lies in its potential to enhance landslide risk assessment and management strategies in mountainous regions. By integrating remote sensing and GIS technologies, the project aims to provide detailed insights into the spatial distribution of landslide susceptibility factors, enabling stakeholders to make informed decisions on land-use planning, disaster preparedness, and infrastructure development. The expected outcomes of this research include the development of a landslide susceptibility map highlighting high-risk areas within the study region. The findings will contribute to the existing knowledge of landslide dynamics and provide valuable information for local authorities, land managers, and disaster response agencies. Additionally, the project will demonstrate the utility of remote sensing and GIS techniques in assessing natural hazards and informing sustainable land management practices. In conclusion, the analysis of landslide susceptibility using remote sensing and GIS techniques in a mountainous region represents a valuable contribution to the field of geoscience and disaster risk reduction. By leveraging advanced technologies and spatial analysis tools, this research aims to improve our understanding of landslide processes and support effective mitigation measures in vulnerable areas.