Thesis Abstract

Abstract
Landslides pose significant threats to lives, infrastructure, and the environment in mountainous regions worldwide. In this thesis, an in-depth analysis of landslide susceptibility in a mountainous region is conducted using advanced Remote Sensing and Geographic Information System (GIS) techniques. The study aims to enhance the understanding of landslide susceptibility factors and develop a robust model for landslide risk assessment and management. The thesis begins with a comprehensive introduction that provides the background of the study, highlights the problem statement, outlines the objectives, discusses the limitations and scope of the study, emphasizes the significance of the research, and provides the structure of the thesis. The definitions of key terms related to landslides, susceptibility, Remote Sensing, and GIS are also presented to ensure clarity and understanding throughout the research. Chapter Two delves into the literature review, examining existing studies on landslide susceptibility assessment, Remote Sensing applications in landslide studies, GIS techniques for analyzing landslide data, and relevant risk assessment models. The review synthesizes key findings, identifies research gaps, and establishes the theoretical framework for the current study. Chapter Three details the research methodology employed, including data collection methods, Remote Sensing data acquisition techniques, GIS data processing procedures, selection of landslide susceptibility factors, model development, validation techniques, and statistical analyses. The chapter also discusses the study area characteristics, data sources, and tools utilized in the research process. Chapter Four presents a thorough discussion of the findings obtained from the analysis of landslide susceptibility in the mountainous region. The chapter evaluates the effectiveness of the developed model, identifies the most influential factors contributing to landslide susceptibility, and assesses the accuracy of the predictive model. Detailed maps, charts, and statistical analyses are used to illustrate the results and facilitate interpretation. In Chapter Five, the conclusion and summary of the research thesis are provided, highlighting the key findings, implications for landslide risk management, recommendations for future research, and the overall contribution of the study to the field of geoscience. The thesis concludes with a call to action for improved landslide monitoring, early warning systems, and sustainable land use planning in mountainous regions. In conclusion, this thesis contributes to the advancement of knowledge in landslide susceptibility analysis through the integration of Remote Sensing and GIS technologies. The findings offer valuable insights for policymakers, land managers, and researchers to mitigate landslide risks and enhance disaster resilience in mountainous regions. Further research is recommended to refine the model, incorporate real-time data, and assess the long-term effectiveness of landslide mitigation strategies.

Thesis Overview

The project titled "Analysis of Landslide Susceptibility in a Mountainous Region Using Remote Sensing and GIS Techniques" aims to address the critical issue of landslides in mountainous regions by employing advanced technologies such as Remote Sensing and Geographic Information Systems (GIS). Landslides are natural hazards that pose significant risks to communities living in mountainous areas. Understanding the factors that contribute to landslide susceptibility is essential for effective risk management and mitigation strategies. Remote Sensing and GIS techniques offer valuable tools for analyzing terrain characteristics, land cover, and environmental factors that influence landslide occurrence. The research will begin with a comprehensive literature review to explore existing studies on landslide susceptibility assessment methods, remote sensing applications, and GIS techniques in similar contexts. This will provide a solid foundation for the research methodology and data analysis approach. The methodology will involve collecting remote sensing data such as satellite imagery and LiDAR (Light Detection and Ranging) data to extract terrain features and land cover information. GIS software will be used to integrate these data layers and analyze the spatial relationships between landslide occurrences and various environmental variables. The study area will be selected based on the prevalence of landslides and the availability of relevant data. The research will focus on identifying key factors contributing to landslide susceptibility, such as slope steepness, soil type, land cover, precipitation patterns, and seismic activity. The findings of the study will be presented through detailed spatial analysis and mapping of landslide susceptibility zones in the study area. These results will provide valuable insights for land use planning, disaster risk reduction, and emergency response strategies in mountainous regions prone to landslides. Overall, this research project aims to contribute to the scientific understanding of landslide susceptibility in mountainous regions and demonstrate the effectiveness of Remote Sensing and GIS technologies in assessing and mapping landslide hazards. By identifying high-risk areas and potential triggers of landslides, the study will support informed decision-making and proactive measures to mitigate the impacts of landslides on vulnerable communities.