Local variations of landslide factors in Pulau Pinang, Malaysia

Abstract

A landslide is one of the most notorious natural disasters, resulting in massive losses and significant damages. Thus, this paper aims to analyze the spatial heterogeneity of the influencing factors which later inspect the relationship between the factors and landslide occurrences. A total of 988 landslides historical data and eight landslide factors were obtained from proper field validation and maps provided by those concerned in the government, including distance to roads, distance to rivers, distance to faults, slope angle, curvature, slope aspect, land use, and lithology. Geographically Weighted Logistic Regression (GWLR) is introduced in this paper to carry out the local analysis, resulting in the slope angle and the slope aspect playing the most significant role in influencing landslides. The Akaike's information criterion (AICc) of GWLR is 824.51 which has a lower value than the global regression represented as 906.09 revealing that GWLR is the best model. Other evaluation criteria such as deviance, local percent deviance explained (pdev), and Bayesian information criterion (BIC) also validate the significance of the GWLR model. The GWLR results show the degree of spatial variation in the relationship between landslides and the influencing factors in the study area as the coefficient values of every factor are inconsistent, providing a reference for managers to formulate targeted decision-making measures. In the meantime, urgent action to sustain this natural disaster as suggested in the SDG 13 has to be taken earnestly to avoid bigger impacts on both society and the environment.