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Analysis of Landslide Susceptibility Using Remote Sensing and Geographic Information Systems (GIS) in a Mountainous Region

 

Table Of Contents


Chapter ONE

: Introduction 1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter TWO

: Literature Review 2.1 Overview of Landslides
2.2 Remote Sensing Applications in Geo-science
2.3 GIS Techniques in Landslide Analysis
2.4 Previous Studies on Landslide Susceptibility
2.5 Factors Influencing Landslide Occurrence
2.6 Landslide Inventory Mapping
2.7 Landslide Susceptibility Mapping Methods
2.8 Machine Learning Approaches in Landslide Analysis
2.9 Case Studies on Landslide Analysis
2.10 Summary of Literature Review

Chapter THREE

: Research Methodology 3.1 Research Design
3.2 Study Area Description
3.3 Data Collection Methods
3.4 Remote Sensing Data Acquisition
3.5 GIS Data Preparation and Processing
3.6 Landslide Inventory Compilation
3.7 Landslide Susceptibility Mapping Techniques
3.8 Model Validation and Accuracy Assessment

Chapter FOUR

: Discussion of Findings 4.1 Overview of Data Analysis
4.2 Landslide Susceptibility Mapping Results
4.3 Comparison of Different Methodologies
4.4 Factors Contributing to Landslide Susceptibility
4.5 Interpretation of Results
4.6 Discussion on Model Performance
4.7 Implications of Findings
4.8 Recommendations for Future Studies

Chapter FIVE

: Conclusion and Summary 5.1 Summary of Findings
5.2 Achievements of the Study
5.3 Conclusion
5.4 Contributions to Geo-science
5.5 Recommendations for Practical Applications
5.6 Suggestions for Further Research

Thesis Abstract

Abstract
Landslides are a common natural hazard in mountainous regions, causing significant damage to infrastructure, property, and human lives. In recent years, the integration of remote sensing and Geographic Information Systems (GIS) has provided new opportunities for assessing and mapping landslide susceptibility. This thesis presents an in-depth analysis of landslide susceptibility using remote sensing and GIS techniques in a mountainous region. The study area selected for this research is characterized by steep slopes, diverse geological formations, and a history of landslide occurrences. The research begins with a comprehensive introduction that outlines the background of the study, the problem statement, objectives, limitations, scope, significance, structure of the thesis, and key definitions of terms. The literature review in Chapter Two critically examines existing studies on landslide susceptibility assessment, remote sensing technologies, GIS applications, and relevant methodologies. The review highlights the significance of integrating remote sensing and GIS for landslide susceptibility mapping and identifies gaps in current research that this study aims to address. Chapter Three details the research methodology employed in this study, including data collection techniques, preprocessing procedures, landslide inventory mapping, terrain analysis, and the application of statistical models for susceptibility assessment. The methodology section discusses the use of satellite imagery, digital elevation models, and field surveys to gather relevant data for the analysis. The findings and results of the study are presented in Chapter Four, where the landslide susceptibility map is generated using the selected remote sensing and GIS techniques. The analysis of the spatial distribution of landslides and the identification of susceptibility factors provide valuable insights for understanding landslide dynamics in the study area. The discussion section interprets the findings, evaluates the accuracy of the susceptibility map, and highlights the implications for landslide risk management and land-use planning. Finally, Chapter Five offers a comprehensive conclusion and summary of the thesis, emphasizing the key findings, contributions to the field of geoscience, and recommendations for future research. The conclusion reflects on the effectiveness of remote sensing and GIS in landslide susceptibility analysis and underscores the importance of proactive measures to mitigate landslide risks in mountainous regions. Overall, this thesis contributes to the growing body of knowledge on landslide susceptibility assessment and provides practical insights for disaster risk reduction and sustainable land management in mountainous areas.

Thesis Overview

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