Thesis Abstract

Abstract
This thesis presents a comprehensive study on the analysis of landslide susceptibility utilizing Geographic Information System (GIS) and remote sensing techniques in a specific region. Landslides are a prevalent natural hazard that poses significant risks to human lives, infrastructure, and the environment. The integration of GIS and remote sensing technologies offers a powerful approach to assess and predict landslide susceptibility, providing valuable insights for risk mitigation and management strategies. The research begins with an introduction discussing the significance of studying landslide susceptibility, followed by a detailed background of the study outlining the current state of research in the field. The problem statement highlights the necessity for accurate and efficient methods to assess landslide susceptibility, leading to the formulation of research objectives aimed at investigating the factors influencing landslide occurrence in the specific region under study. The methodology chapter describes the research design, data collection techniques, and the application of GIS and remote sensing tools for analyzing landslide susceptibility. Various spatial analysis methods, including terrain analysis, land cover classification, and slope stability modeling, are employed to identify areas at high risk of landslides. The research methodology also encompasses field validation to assess the accuracy of the predictive models developed using GIS and remote sensing data. Chapter four presents a detailed discussion of the findings obtained from the analysis of landslide susceptibility in the specific region. The spatial distribution of landslides, the influence of topographic factors, land cover characteristics, and other environmental variables on landslide occurrence are thoroughly examined. The results provide valuable insights into the factors contributing to landslide susceptibility, enabling the identification of high-risk zones and the development of effective mitigation strategies. Finally, the conclusion chapter summarizes the key findings of the study and discusses the implications for landslide risk assessment and management in the specific region. The research contributes to the existing knowledge on landslide susceptibility analysis by demonstrating the effectiveness of GIS and remote sensing techniques in predicting and mapping landslide-prone areas. The study underscores the importance of incorporating spatial data analysis tools in landslide risk assessment to enhance preparedness and resilience against this natural hazard. In conclusion, this thesis offers a comprehensive analysis of landslide susceptibility using GIS and remote sensing techniques in a specific region, providing valuable insights for decision-makers, urban planners, and disaster management authorities. The research findings contribute to the advancement of landslide risk assessment methodologies and highlight the potential of spatial analysis tools in enhancing hazard mitigation efforts. Keywords Landslide susceptibility, Geographic Information System (GIS), Remote sensing, Spatial analysis, Risk assessment, Hazard mitigation.

Thesis Overview

The research project titled "Analysis of landslide susceptibility using GIS and remote sensing techniques in a specific region" aims to investigate and analyze the factors contributing to landslide occurrences in a particular geographical area through the application of Geographic Information System (GIS) and remote sensing technologies. Landslides are a significant geological hazard that poses risks to human life, infrastructure, and the environment. By utilizing advanced GIS and remote sensing tools, this study seeks to enhance the understanding of landslide susceptibility in the chosen region and provide valuable insights for effective risk management and mitigation strategies. The research will begin with a comprehensive literature review to establish the current knowledge and research gaps related to landslide susceptibility assessment, GIS, and remote sensing applications in landslide studies. This review will serve as the foundation for the research methodology, ensuring a sound and systematic approach to data collection, analysis, and interpretation. Various studies on landslide susceptibility mapping methodologies, including the integration of GIS and remote sensing data, will be critically examined to identify the most suitable techniques for the specific region under study. The methodology section will detail the data sources, including satellite imagery, digital elevation models, geological maps, land cover data, and topographic data, which will be utilized to identify and analyze landslide-prone areas. GIS software will be employed to process and analyze the data, allowing for the creation of landslide susceptibility maps that highlight areas at high risk of landslide occurrence. Remote sensing techniques, such as image classification and change detection, will be used to monitor land cover changes and identify factors contributing to landslide susceptibility, such as deforestation, land use changes, and slope instability. The findings of the research will be presented in the discussion section, where the results of the GIS and remote sensing analyses will be interpreted and discussed in relation to existing literature and theoretical frameworks. The spatial distribution of landslide susceptibility zones will be mapped and analyzed, providing valuable information for land use planning, disaster preparedness, and risk reduction initiatives in the study area. The factors influencing landslide susceptibility, including topography, geology, land cover, and human activities, will be identified and prioritized based on their impact on landslide occurrence. In conclusion, this research project aims to contribute to the field of landslide susceptibility assessment by integrating GIS and remote sensing techniques to analyze and map landslide-prone areas in a specific region. The study will provide valuable insights for decision-makers, land use planners, and disaster management agencies to develop effective strategies for mitigating landslide risks and enhancing community resilience. By combining advanced geospatial technologies with geological knowledge, this research seeks to improve our understanding of landslide hazards and support sustainable development practices in regions prone to landslide occurrences.