Analysis of landslide susceptibility in a specific region using GIS and remote sensing techniques.

Thesis Abstract

The abstract is a comprehensive summary of the main points of the thesis, providing a clear overview of the research conducted, the methods employed, and the findings obtained. Below is an abstract for the thesis titled "Analysis of landslide susceptibility in a specific region using GIS and remote sensing techniques." Abstract
Landslides are natural hazards that pose significant risks to human lives, infrastructure, and the environment. Understanding the factors contributing to landslide susceptibility is crucial for effective risk assessment and mitigation strategies. This thesis focuses on the analysis of landslide susceptibility in a specific region through the integration of Geographic Information Systems (GIS) and remote sensing techniques. The study area, located in [specific region], has experienced recurrent landslide events, highlighting the urgent need for a comprehensive analysis to assess susceptibility factors and guide land use planning decisions. The research begins with a detailed review of existing literature on landslide susceptibility assessment methods, GIS applications, and remote sensing technologies. Through a systematic literature review, key factors influencing landslide occurrence, such as topography, geology, land cover, and rainfall patterns, are identified and analyzed. Additionally, the role of GIS and remote sensing in landslide susceptibility mapping is explored, emphasizing their potential to enhance spatial analysis and modeling capabilities. The methodology chapter outlines the research design, data collection procedures, and analytical techniques employed in the study. High-resolution satellite imagery, digital elevation models, and geological maps are utilized to extract relevant spatial data for landslide susceptibility mapping. GIS-based models, such as the Analytical Hierarchy Process (AHP) and Logistic Regression, are applied to integrate multiple factors and generate susceptibility maps for the study area. The validation of the models is conducted using historical landslide records and field surveys to assess the accuracy and reliability of the results. The findings chapter presents the results of the analysis, highlighting the spatial distribution of landslide susceptibility zones in the study area. The susceptibility maps generated through GIS and remote sensing techniques reveal areas at high, moderate, and low risk of landslide occurrence based on the identified factors. The influence of topographic features, land cover types, and geological characteristics on landslide susceptibility is examined, providing valuable insights for land management and disaster preparedness. In conclusion, this thesis contributes to the understanding of landslide susceptibility assessment in the specific region by utilizing advanced GIS and remote sensing tools. The integration of spatial data and analytical models enables the identification of vulnerable areas and the prioritization of mitigation measures to reduce landslide risks. The significance of this research lies in its practical implications for land use planning, disaster risk reduction, and sustainable development in landslide-prone regions. Keywords Landslide susceptibility, Geographic Information Systems (GIS), Remote sensing, Analytical Hierarchy Process (AHP), Logistic Regression, Risk assessment, Spatial analysis, Disaster management, Sustainable development.