Project Abstract

Abstract
Geographic Information Systems (GIS) have revolutionized the field of geoscience by providing powerful tools for analyzing and visualizing spatial data. Landslides are a significant natural hazard that can have devastating impacts on communities, infrastructure, and the environment. Understanding the susceptibility of an area to landslides is crucial for effective land use planning, risk assessment, and disaster management. This research project focuses on the application of GIS in landslide susceptibility mapping to enhance our ability to predict and mitigate landslide hazards. The study begins with a comprehensive introduction that highlights the importance of landslide susceptibility mapping and the role of GIS in this process. The background of the study provides a review of relevant literature on landslides, GIS technology, and previous research on landslide susceptibility mapping. The problem statement identifies the gaps in existing knowledge and the need for improved methodologies in landslide susceptibility assessment. The objectives of the study are to develop a robust GIS-based methodology for landslide susceptibility mapping, to apply this methodology in a case study area, and to evaluate its effectiveness in predicting landslide occurrences. The limitations of the study are acknowledged, including data availability, scale of analysis, and uncertainties associated with the modeling process. The scope of the study defines the geographical extent and characteristics of the study area, as well as the types of landslides considered. The significance of the study lies in its potential to enhance landslide risk assessment and management practices by providing detailed spatial information on landslide susceptibility. The structure of the research outlines the organization of the study, including the chapters on literature review, research methodology, discussion of findings, and conclusion. The literature review chapter critically analyzes existing research on landslide susceptibility mapping, GIS applications in landslide studies, and relevant methodologies for assessing landslide hazards. Key themes explored include terrain analysis, hydrological modeling, remote sensing techniques, and statistical approaches to landslide susceptibility mapping. The research methodology chapter details the step-by-step process of data collection, preprocessing, analysis, and modeling for landslide susceptibility mapping. Methods such as data acquisition, terrain analysis, slope stability modeling, and validation techniques are described in depth. The chapter also discusses the selection of input variables, model calibration, and sensitivity analysis. The discussion of findings chapter presents the results of the landslide susceptibility mapping exercise, including spatial maps, statistical analyses, and validation metrics. The effectiveness of the GIS-based methodology in predicting landslide occurrences is evaluated, and the implications of the findings for landslide risk management are discussed. In conclusion, the study highlights the potential of GIS technology in improving our understanding of landslide susceptibility and enhancing our ability to assess and mitigate landslide hazards. Recommendations for future research and practical applications of the study findings are provided. Overall, this research contributes to the growing body of knowledge on landslide susceptibility mapping and demonstrates the value of GIS in geoscience research and natural hazard assessment.

Project Overview