Thesis Abstract

Abstract
Landslides present a significant natural hazard that can result in devastating consequences for communities and infrastructure. The use of remote sensing and Geographic Information Systems (GIS) has emerged as a valuable tool for assessing landslide susceptibility and mitigating risks associated with these hazardous events. This thesis focuses on the assessment of landslide susceptibility using remote sensing and GIS techniques, with the aim of providing a comprehensive understanding of the factors contributing to landslide occurrence. The research begins with an introduction that highlights the importance of studying landslide susceptibility and the role of remote sensing and GIS in this field. The background of the study provides context for the research by discussing previous studies on landslide susceptibility assessment and the limitations of existing methodologies. The problem statement identifies the gaps in current approaches and underscores the need for a more comprehensive and accurate assessment of landslide susceptibility. The objectives of the study are to develop a methodology for assessing landslide susceptibility using remote sensing and GIS techniques, identify key factors influencing landslide occurrence, and create a susceptibility map to help in landslide risk management. The limitations of the study are also discussed to provide a clear understanding of the scope and potential constraints of the research. The methodology chapter outlines the research approach, data collection methods, and analytical techniques used to assess landslide susceptibility. Remote sensing data, including satellite imagery and digital elevation models, are utilized to extract relevant information for the analysis. GIS tools are employed to integrate and analyze the data to identify areas at high risk of landslides. The findings chapter presents the results of the analysis, including the identification of key factors contributing to landslide susceptibility and the development of a susceptibility map. The discussion explores the implications of the findings and their relevance for landslide risk management and mitigation strategies. In conclusion, this thesis contributes to the field of landslide susceptibility assessment by demonstrating the effectiveness of remote sensing and GIS techniques in identifying areas at high risk of landslides. The significance of the study lies in its potential to inform decision-making processes and improve the resilience of communities facing landslide hazards. Overall, this research underscores the importance of utilizing advanced technologies for assessing and managing landslide susceptibility in a proactive and effective manner.

Thesis Overview