Landslide Susceptibility Mapping In Tadian, Mountain Province

Abstract

Landslides are significant natural hazard in Tadian, Mountain Province, posing substantial risks to life, property, and infrastructure. This study aimed to develop a comprehensive landslide susceptibility map for Tadian using Logistic Regression analysis in R Studio and Geographic Information System (GIS) technology. Various factors influencing landslide occurrences were analyzed, including historical landslide locations, aspect, elevation, lithology, land cover, precipitation, slope, soil texture, NDVI, road network, and river network. Data collection involved gathering historical landslide records, topographic and geological maps, remote sensing data for land cover and NDVI, meteorological precipitation records, and

infrastructure maps. These datasets were integrated into GIS to produce thematic maps representing each factor. Logistic Regression analysis was then performed to model the probability of landslides based on these inputs, resulting in a landslide susceptibility map depicting the locations of the susceptible zones.

The results indicated that steep slopes, high precipitation, specific lithological units, and proximity to roads and rivers significantly increase landslide susceptibility. Conversely, areas with dense vegetation showed lower susceptibility, highlighting the protective role of forest cover. The model's accuracy was validated against historical landslide data, demonstrating a strong correlation between predicted landslide risk zones and past landslide occurrences. Given these findings, the study concludes that logistic regression and GIS are effective tools for landslide susceptibility mapping, providing valuable insights for risk assessment and management. The generated map serves as a critical resource for local authorities and planners in Tadian, guiding land use planning, infrastructure development, and disaster preparedness.

 Recommendations include enhancing monitoring systems, implementing slope stabilization measures, promoting reforestation, educating communities about landslide risks further researches on the other factors considered in the study. Regular updates to the susceptibility map, incorporating new data and advanced modeling techniques, are essential for ongoing risk mitigation.

This research contributes to a deeper understanding of landslide dynamics in Tadian, ultimately aiding in the development of strategies to enhance community resilience and safety in the face of natural hazards.