Landslide Susceptibility Mapping Utilizing the Weighted Frequency Ratio Technique: A Case Study of Klang Valley, Malaysia

Abstract

The escalating impacts of climate change have intensified slope instability and increased landslide occurrences in the rapidly urbanizing Klang Valley, Malaysia. With more intense rainfall and rising temperatures, the region faces unprecedented challenges to soil and slope stability due to rapid urbanization. This study evaluates landslide susceptibility by analyzing rainfall and temperature as primary triggering factors, alongside parameters such as elevation, slope angle, aspect, curvature, lithology, land use, soil properties, and NDVI. Key findings highlight that land use, particularly in commercial, industrial, and infrastructure areas with high FR (9.44) and LSI (2.627), significantly influences landslide susceptibility due to construction and terrain alterations. Steep slopes are especially vulnerable as they accelerate runoff, while areas with low NDVI, indicative of sparse vegetation, are more prone to slope failures due to the stabilizing role of vegetation. Regions characterized by vein quartz (FR=6.31; LSI=0.801), known for its brittle structure, and mined lands disturbed by human activities, also exhibit heightened geological vulnerabilities. Utilizing bivariate regression and the Weighted Frequency Ratio (WFR) method in ArcGIS, the study integrates high-resolution LiDAR and digital terrain models (DTMs) to develop a detailed and accurate landslide susceptibility map. These findings offer critical insights for disaster risk reduction strategies and climate-resilient urban planning in the Klang Valley, aligning with United Nations Sustainable Development Goal (SDG) 13.