Project Abstract

Abstract
Landslides pose a significant threat to communities and infrastructure in various regions worldwide. The accurate assessment of landslide susceptibility is crucial for effective risk management and mitigation strategies. This research project focuses on the analysis of landslide susceptibility in a specific region utilizing remote sensing and Geographic Information System (GIS) techniques. The study aims to identify the factors contributing to landslide occurrence and develop a predictive model to assess susceptibility levels. The research begins with a comprehensive introduction, providing background information on landslides and the importance of studying susceptibility in the selected region. The problem statement highlights the need for a systematic approach to assess landslide susceptibility, emphasizing the potential risks and impacts associated with these natural hazards. The objectives of the study include identifying key factors influencing landslide occurrence, mapping susceptibility zones, and evaluating the effectiveness of remote sensing and GIS techniques in landslide analysis. Limitations of the study are acknowledged, such as data availability, scale limitations, and uncertainties inherent in predictive modeling. The scope of the study defines the boundaries and extent of the research, focusing on a specific region known for landslide occurrences. The significance of the study lies in its potential to enhance hazard mapping and risk assessment, contributing to the development of more resilient communities and infrastructure. The research methodology encompasses various steps, including data collection, preprocessing, feature selection, model development, and validation. Remote sensing data, such as satellite imagery and digital elevation models, are utilized to extract relevant terrain attributes and land cover information. GIS tools are employed to integrate spatial data and analyze the relationships between landslide occurrence and influencing factors. The literature review explores existing studies on landslide susceptibility assessment, remote sensing applications, GIS techniques, and predictive modeling approaches. The discussion covers key concepts, methodologies, and findings from previous research to provide a comprehensive background for the current study. Findings from the analysis reveal spatial patterns of landslide susceptibility in the study area, highlighting high-risk zones and vulnerable areas. The discussion delves into the factors contributing to landslide occurrence, including topography, geology, land cover, and land use changes. The results of the predictive model are evaluated for accuracy and reliability, emphasizing the importance of validation and uncertainty analysis in landslide susceptibility mapping. In conclusion, this research project contributes to the understanding of landslide susceptibility in the specific region through the application of remote sensing and GIS techniques. The study provides valuable insights into the factors influencing landslide occurrence and offers a predictive model for assessing susceptibility levels. The research findings can inform decision-makers, land use planners, and emergency responders in developing proactive measures to mitigate landslide risks and enhance community resilience. Keywords Landslide susceptibility, Remote sensing, GIS, Predictive modeling, Hazard mapping, Risk assessment, Spatial analysis, Natural hazards.

Project Overview