Catastrophe theory and AHP modelling of landslide susceptibility using multi-source geodata in southwestern Nigeria

Landslides are among the most destructive natural hazards in mountainous and structurally complex terrains, posing significant threats to lives, infrastructure, and sustainable development. Accurate Landslide Susceptibility Mapping (LSM) is therefore essential for hazard mitigation and land-use planning. This study develops a Catastrophe Theory (CT)-based Landslide Susceptibility Mapping Index (LSMI) that integrates surface and subsurface conditioning factors derived from geological, geomorphological, geophysical, and climatic datasets. Unlike conventional approaches that rely primarily on expert judgment or data-intensive machine-learning algorithms, the proposed framework employs Catastrophe Theory and fuzzy membership transformation to derive factor weights through catastrophe normalization functions, thereby reducing subjectivity in the weighting process. Nine landslide conditioning factors, including slope, elevation, lithology, rainfall, lineament density, drainage density, transverse resistance, coefficient of anisotropy, and bedrock topography, were integrated within a GIS environment to generate a CT-based susceptibility model and compared with an Analytical Hierarchy Process (AHP)-based model. The results revealed distinct factor-ranking patterns between the two approaches, reflecting their different weighting philosophies. While AHP emphasized surface geomorphological controls, particularly slope, CT assigned the highest weight to transverse resistance, highlighting the influence of subsurface weathering, groundwater conditions, and rock competence on slope instability. The resulting susceptibility maps were classified into five categories and validated using landslide inventory data and Receiver Operating Characteristic (ROC) analysis. The CT model achieved an Area Under the Curve (AUC) value of 0.74, outperforming the AHP model (AUC = 0.63). These findings demonstrate that integrating subsurface geophysical information with Catastrophe Theory provides a promising complementary framework for landslide susceptibility assessment in structurally complex Basement Complex terrains, although further validation in different geological settings is recommended. Graphical Abstract