Project Abstract

Abstract
Landslides are a common natural hazard that poses significant risks to human lives and infrastructure globally. The application of advanced technologies such as remote sensing and Geographic Information Systems (GIS) has become increasingly vital in the analysis and prediction of landslide susceptibility. This research aims to investigate the factors influencing landslide susceptibility in a specific region through the integration of remote sensing and GIS techniques. The specific objectives include identifying the key factors contributing to landslide occurrence, developing a landslide susceptibility map, and assessing the effectiveness of remote sensing and GIS in landslide analysis. Chapter 1 provides an introduction to the research topic, the background of the study, problem statement, objectives, limitations, scope, significance, structure of the research, and definition of terms. Chapter 2 presents a comprehensive literature review on landslide susceptibility assessment, remote sensing, GIS applications in landslide analysis, and relevant studies in the field. Chapter 3 outlines the research methodology, including data collection, preprocessing, analysis techniques, and model development. The research methodology encompasses the collection of satellite imagery, digital elevation models, land cover data, and geological information for the study area. Various remote sensing techniques such as image classification, change detection, and spectral analysis will be employed to extract relevant information for landslide susceptibility analysis. GIS tools will be utilized for spatial data integration, analysis, and modeling. The research methodology also includes statistical analysis and the development of a predictive model for landslide susceptibility assessment. Chapter 4 presents the detailed discussion of findings, including the identification of landslide-prone areas, the relationship between contributing factors and landslide occurrence, and the accuracy of the developed susceptibility model. The results will be critically analyzed and compared with existing studies to assess the efficacy of remote sensing and GIS techniques in landslide analysis. Furthermore, the implications of the findings for land use planning, disaster risk reduction, and mitigation strategies will be discussed. Finally, Chapter 5 provides a conclusion and summary of the research project, highlighting the key findings, implications, and recommendations for future research. The research findings will contribute to enhancing our understanding of landslide susceptibility and improving disaster management strategies in the study region. The integration of remote sensing and GIS technologies offers a powerful tool for assessing landslide susceptibility and supporting decision-making processes in landslide-prone areas.

Project Overview