A Review on Landslide Susceptibility Mapping in Malaysia: Recent Trend and Approaches

Abstract

The accelerating economic growth has assisted rapid urban development and expansion of construction sites into the landslide-vulnerable zones in Malaysia. Thus landslide susceptibility mapping has now become an important part of project designing work for landslide zone areas. There are several models that are used for susceptibility mapping, especially in the peninsular region. Every model has its own set of selected computing variables and characteristics to generate a map. To date, there is no single method applicable to assess and predict all landslides, as there are variations of geomorphological conditions set by the nature. This paper has reviewed recent research publications on landslide susceptibility mapping in Malaysia. Results show that there are 16 models that are being used to describe landslide risk mapping and among them, the Fuzzy model, Neural Network combined with Fuzzy logic, evidential belief function model, probability analysis (e.g. Weights-of-Evidence, and regression), and Support Vector Machine models are proved to be effective even in the areas with limited information. It is observed that most of the susceptible models use curvature, slope angles, distance from drainage, altitude, slope gradient, road distance, aspects as variable factors, and prolonged rainfall as the prime triggering factors. Furthermore, it is observed that the maximum number of research has been conducted in Cameron Highlands (28%) and Penang (20%), because of their high frequencies of landslide occurring and vulnerabilities. Sabah and Sarawak are covered by a negligible number of susceptibility research. Further, a comparison study between the selected models presents the limitations of each model and their benefits and some suggestions are also made based on the author's recommendations works.