Thesis Abstract

Abstract
This thesis focuses on the analysis of landslide risk assessment in a mountainous region utilizing remote sensing techniques. Landslides are significant natural hazards that can cause severe damage to infrastructure, loss of life, and disruption to communities. Traditional methods of landslide risk assessment are often time-consuming, labor-intensive, and may lack spatial accuracy. Remote sensing technologies offer a promising alternative for assessing landslide risk due to their ability to capture detailed spatial information over large areas. This research aims to investigate the feasibility and effectiveness of using remote sensing techniques for landslide risk assessment in a mountainous region. The study begins with an introduction providing background information on landslides, their causes, and the importance of accurate risk assessment. The problem statement highlights the limitations of current methods and the need for more efficient and accurate approaches. The objectives of the study are outlined to guide the research process towards developing a comprehensive landslide risk assessment framework using remote sensing technologies. The literature review chapter critically examines existing studies on landslide risk assessment, remote sensing applications, and methodologies for analyzing terrain stability in mountainous regions. Key themes explored include the role of topographic factors, land cover characteristics, and environmental parameters in influencing landslide susceptibility. The chapter also reviews the use of various remote sensing techniques such as satellite imagery, LiDAR, and unmanned aerial vehicles (UAVs) for landslide detection and monitoring. The research methodology chapter presents a detailed overview of the methodological approach adopted in this study. It covers data collection procedures, image processing techniques, and the development of a geospatial model for landslide risk assessment. The chapter also discusses the selection of study area, data sources, and validation methods employed to assess the accuracy of the remote sensing-based risk assessment model. The findings chapter presents the results of the analysis conducted to assess landslide risk in the mountainous region using remote sensing techniques. The discussion focuses on the identification of high-risk zones, the factors influencing landslide susceptibility, and the validation of the risk assessment model. The chapter also highlights the strengths and limitations of the remote sensing approach and provides recommendations for future research and practical applications. In conclusion, this thesis demonstrates the potential of remote sensing techniques for improving landslide risk assessment in mountainous regions. The study contributes to the advancement of geospatial technologies in natural hazard management and provides valuable insights for policymakers, land use planners, and emergency response agencies. The findings of this research can inform decision-making processes aimed at reducing the impact of landslides and enhancing the resilience of communities living in high-risk areas.

Thesis Overview

The project titled "Analysis of Landslide Risk Assessment in a Mountainous Region Using Remote Sensing Techniques" aims to investigate and analyze the factors influencing landslide occurrences in mountainous regions. Landslides are a significant natural hazard that can cause devastating effects on the environment, infrastructure, and human lives. Mountainous regions are particularly susceptible to landslides due to factors such as steep slopes, geological conditions, and intense rainfall. Remote sensing techniques offer a valuable tool for assessing landslide risks by providing detailed information on terrain characteristics, land cover, and land use patterns. This research will utilize remote sensing data, including satellite imagery, LiDAR (Light Detection and Ranging) data, and digital elevation models, to analyze landslide-prone areas in a mountainous region. By integrating these datasets with Geographic Information System (GIS) technology, the study aims to identify high-risk zones and assess the vulnerability of the area to landslides. The research will begin with a comprehensive literature review to explore existing methods and approaches for landslide risk assessment using remote sensing techniques. This review will provide a theoretical framework for the study and help identify gaps in current knowledge that the research aims to address. The methodology will involve data collection, processing, and analysis to develop a landslide susceptibility map for the study area. Key components of the research methodology will include terrain analysis, land cover classification, and slope stability modeling. Terrain analysis will involve the extraction of topographic features such as slope angle, aspect, and elevation from the remote sensing data. Land cover classification will identify different land cover types in the study area to assess their influence on landslide susceptibility. Slope stability modeling will evaluate the stability of slopes based on factors such as soil characteristics, rainfall intensity, and land use practices. The findings of the study will be presented and discussed in detail to highlight the spatial distribution of landslide-prone areas and the factors contributing to landslide risk in the mountainous region. The discussion will also address the limitations of the study, such as data availability and accuracy, and propose recommendations for future research and practical applications. The research will conclude with a summary of the key findings, implications for landslide risk management, and suggestions for further research in the field of landslide risk assessment using remote sensing techniques.