Thesis Abstract

**Abstract
** This thesis presents a comprehensive analysis of Landslide Risk Assessment utilizing cutting-edge Remote Sensing and Geographic Information System (GIS) techniques. Landslides are natural hazards that pose significant threats to communities and infrastructures worldwide. The integration of Remote Sensing data and GIS technologies provides a powerful tool for assessing and mitigating landslide risks. This research aims to develop a robust methodology for identifying potential landslide-prone areas, analyzing the factors contributing to landslide occurrence, and ultimately enhancing landslide risk assessment strategies. The study begins with an exploration of the existing literature on landslides, remote sensing applications, and GIS techniques. It establishes a solid foundation for understanding the complexities of landslide processes and the role of technology in risk assessment. The literature review highlights key studies, methodologies, and tools relevant to landslide risk assessment, providing insights into current practices and areas for improvement. The research methodology section outlines the step-by-step approach employed in this study. It encompasses data collection, preprocessing, analysis, and modeling techniques used to assess landslide risks. Remote Sensing data, including satellite imagery, LiDAR data, and aerial photographs, are integrated into GIS platforms to extract relevant information on terrain characteristics, land cover, and other factors influencing landslide susceptibility. Various statistical and spatial analysis tools are utilized to quantify landslide risks and develop predictive models. The findings from the study are discussed in detail in Chapter Four, where the results of the landslide risk assessment are presented and analyzed. The study identifies high-risk areas prone to landslides based on the integrated Remote Sensing and GIS analysis. The factors contributing to landslide susceptibility, such as slope gradient, soil type, land use, and rainfall patterns, are evaluated to understand the underlying mechanisms of landslide occurrence. The discussion also includes the validation of the risk assessment models and the implications of the findings for landslide mitigation and management. In conclusion, this thesis provides valuable insights into the application of Remote Sensing and GIS techniques for landslide risk assessment. The research contributes to the existing knowledge base on landslide hazards and provides practical tools for assessing and managing landslide risks. The significance of this study lies in its potential to aid decision-makers, urban planners, and disaster management authorities in developing effective strategies to mitigate the impacts of landslides on vulnerable communities. The findings of this research can inform land use planning, infrastructure development, and disaster preparedness efforts to enhance resilience to landslide hazards. Overall, this thesis offers a comprehensive analysis of Landslide Risk Assessment using Remote Sensing and GIS techniques, highlighting the importance of integrating technology and geospatial data for effective risk management. The research outcomes have implications for disaster risk reduction, environmental planning, and sustainable development, emphasizing the critical role of innovative technologies in addressing natural hazards and enhancing community resilience.

Thesis Overview