Project Abstract

Abstract
Landslides are natural hazards that pose significant risks to lives, infrastructure, and the environment in many regions worldwide. In this research study, the assessment of landslide susceptibility in a specific region using Geographic Information System (GIS) and remote sensing techniques is conducted to enhance understanding and mitigation strategies for landslide occurrences. The research aims to identify the factors influencing landslide susceptibility and develop a reliable model for predicting potential landslide-prone areas within the study region. The study begins with a comprehensive introduction highlighting the significance of assessing landslide susceptibility and the role of GIS and remote sensing in landslide studies. The background of the study provides a detailed overview of landslides, their causes, impacts, and existing methods for landslide susceptibility assessment. The problem statement emphasizes the need for a more accurate and efficient approach to assess landslide susceptibility, considering the limitations of traditional methods. The objectives of the study include identifying the key factors contributing to landslide susceptibility, developing a GIS-based model for landslide susceptibility mapping, and validating the model using remote sensing data. The limitations of the study, such as data availability and accuracy, are acknowledged, and the scope of the study focuses on a specific region prone to landslides. The research methodology section outlines the steps taken to achieve the research objectives, including data collection, preprocessing, analysis, and model development. Various remote sensing techniques, such as satellite imagery and LiDAR data, are utilized to extract relevant information for landslide susceptibility assessment. The chapter also discusses the selection of appropriate GIS tools and statistical methods for data analysis. The literature review covers a wide range of studies on landslide susceptibility assessment, GIS modeling, remote sensing applications in landslide studies, and relevant case studies from similar regions. The discussion of findings chapter presents the results of the GIS-based model, highlighting the factors contributing to landslide susceptibility and the accuracy of the model in predicting landslide-prone areas. The conclusion summarizes the key findings of the research, emphasizing the importance of integrating GIS and remote sensing techniques in landslide susceptibility assessment. The study contributes to the existing knowledge by providing a reliable model for identifying areas at high risk of landslides, thereby supporting effective land use planning and disaster management strategies in the study region. In conclusion, this research study demonstrates the effectiveness of GIS and remote sensing techniques in assessing landslide susceptibility and highlights the importance of incorporating these tools into landslide risk management practices. The findings of the study can be utilized by policymakers, planners, and stakeholders to mitigate the impacts of landslides and enhance the resilience of communities in landslide-prone areas.

Project Overview

The research project focuses on the assessment of landslide susceptibility in a specific region through the utilization of Geographic Information System (GIS) and Remote Sensing techniques. Landslides are natural hazards that pose significant risks to communities, infrastructure, and the environment. By employing GIS and Remote Sensing technologies, this study aims to enhance the understanding of the factors contributing to landslide susceptibility and develop predictive models to identify areas prone to landslides in the target region. The project will begin with a comprehensive literature review to explore existing studies, methodologies, and tools related to landslide susceptibility assessment, GIS, and Remote Sensing applications. This review will provide a solid foundation for understanding the key concepts and methodologies employed in similar studies, thereby informing the research methodology and approach adopted in this project. The study area will be carefully selected based on its susceptibility to landslides and the availability of relevant data sources. GIS software will be used to integrate spatial data layers, including topography, geology, land cover, rainfall patterns, and historical landslide occurrences. Remote sensing data, such as satellite imagery and aerial photographs, will be utilized to extract additional information about land surface characteristics and changes over time. The research methodology will involve data collection, processing, analysis, and modeling to assess landslide susceptibility in the study area. Various statistical and spatial analysis techniques will be employed to identify the factors influencing landslide occurrence and develop a susceptibility map that categorizes the region into different risk zones. The findings of the study will be discussed in detail, highlighting the key factors contributing to landslide susceptibility and the effectiveness of GIS and Remote Sensing techniques in assessing and mapping landslide-prone areas. The results will provide valuable insights for land use planning, disaster risk management, and mitigation strategies to reduce the impact of landslides in the specific region. In conclusion, this research project aims to contribute to the field of geohazards assessment by leveraging advanced technologies such as GIS and Remote Sensing to improve landslide susceptibility mapping and risk assessment in a specific region. By enhancing our understanding of landslide dynamics and vulnerabilities, this study seeks to support informed decision-making and proactive measures to mitigate the impacts of landslides on human lives and infrastructure.