Landslides pose a significant threat to communities, infrastructure, and the environment. Accurate landslide susceptibility mapping is crucial for effective risk management and mitigation strategies. This study aimed to generate an enhanced landslide susceptibility map for the municipality of Sta. Fe, Nueva Vizcaya, Philippines, using Geographic Information System (GIS) and the Analytical Hierarchy Process (AHP). The study examined the relationship between landslide occurrence and various causative factors, including slope, elevation, soil type, land cover, distance from roads and rivers, and rainfall.

The primary five contributing factors were identified, and their relative weights were determined using the AHP. The enhanced landslide susceptibility map was then generated by integrating these factors. The results revealed that slope (35%) and rainfall (23.56%) were the most influential factors, followed by soil type (15.38%), land cover (9.75%), and elevation (7.21%). The enhanced map classified the study area into four susceptibility classes: very low, low, moderate, and high. Approximately 7,330.41 hectares were identified as highly susceptible, 8,469.94 hectares as moderately susceptible, 5,847.56 hectares as low susceptible, and 2,171.32 hectares as very low susceptible to landslides.

Compared to the existing 2019 susceptibility map, the enhanced version showed a significant difference in the distribution of susceptibility classes, highlighting its improved accuracy and reliability.

Research paper (Bachelor of Science in Geodetic Engineering)

Includes appendices and bibliographical references