Mitigating Landslide Hazards in Qena Governorate of Egypt: A GIS-based Neutrosophic PAPRIKA Approach

This paper presents a novel approach to landslide susceptibility assessment in the Qena Governorate, Egypt, integrating the neutrosophic Multi-Criteria Decision-Making (MCDM) method, the Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA), and the ArcGIS weighted overlay technique. The research focuses on the quantification and prioritization of eight criteria: slope, aspect, proximity to road, soil type, proximity to river, land cover, elevation, and Lithology. These factors are evaluated under the uncertainty and indeterminacy of the neutrosophic environment by employing the PAPRIKA method. The results of the analysis are visualized and interpreted using ArcGIS weighted overlay, offering spatially explicit insights into the landslide-prone areas. This study's outcomes could significantly contribute to the overall understanding of landslide hazards in Qena, promoting better hazard management and mitigation strategies. The results of the study demonstrated varying levels of landslide susceptibility within the study area: 2% of the area was identified as having Very High Susceptibility, 17% presented High Susceptibility, 28% had Moderate Susceptibility, 44% indicated Low Susceptibility, 8% showed Very Low Susceptibility, and 1% with Practically No Susceptibility. These findings can aid local authorities and policy-makers in prioritizing areas for mitigation efforts based on their susceptibility to landslides. The study also incorporates a sensitivity analysis, exploring ten different scenarios to ensure the robustness and reliability of the results. In the first scenario, we adhere to our initial criteria weights to represent the current situation. In the second scenario, all criteria are accorded equal significance to check the model's steadfastness when no one criterion outweighs another. Scenarios three to ten each elevate the weightage of one criterion, allowing for a comprehensive understanding of each individual criterion’s influence on the decision-making process. This systematic alteration helps pinpoint the salient features driving landslides and aids in fortifying our mitigation strategies.