Analysis of Landslide Susceptibility Using GIS and Remote Sensing Techniques

Thesis Overview

The research project titled "Analysis of Landslide Susceptibility Using GIS and Remote Sensing Techniques" aims to investigate and assess the factors contributing to landslide susceptibility in a specific geographic area by utilizing Geographic Information System (GIS) and Remote Sensing technologies. Landslides pose a significant threat to communities, infrastructure, and the environment, making it crucial to understand and predict their occurrence to mitigate risks effectively. The study will begin with a comprehensive literature review to explore existing research on landslide susceptibility assessment methods, GIS applications, Remote Sensing techniques, and factors influencing landslides. This review will provide a foundation for understanding the current state of knowledge in the field and identify gaps that the research aims to address. The research methodology will involve collecting relevant data, including topographic, geological, hydrological, and land cover information, which will be integrated into a GIS environment for analysis. Remote Sensing data, such as satellite imagery, will also be utilized to monitor land surface changes and identify potential landslide-prone areas. By applying spatial analysis techniques within the GIS framework, the study will develop a landslide susceptibility model that incorporates various influencing factors. These factors may include slope steepness, soil type, land cover, rainfall patterns, and proximity to roads or infrastructure. The model will be validated using historical landslide data and statistical analysis to assess its accuracy and reliability in predicting landslide susceptibility. The findings of the research will be presented and discussed in detail, highlighting the spatial distribution of landslide susceptibility within the study area and the key factors contributing to landslide occurrence. The implications of these findings for risk assessment, land use planning, and disaster management will be addressed, emphasizing the importance of incorporating GIS and Remote Sensing techniques in landslide mitigation strategies. In conclusion, the research will provide valuable insights into understanding landslide susceptibility and improving risk assessment and management practices through the integration of GIS and Remote Sensing technologies. The study aims to contribute to the body of knowledge on landslide hazard assessment and provide practical recommendations for enhancing resilience to landslides in vulnerable areas.