Mapping slope failure vulnerability in Penang using Artificial Nervous Network (ANN)

Slope failure is an environmental disaster caused by spatial and non-spatial factors, and uncontrolled development aggravates it. In rapidly developing Malaysia mapping slope failures has become part and parcel of disaster prevention and management. Taking into consideration the influence of slope failure column, this paper illustrates the development of a slope failure vulnerability map in Penang using artificial neural networks (ANN) with the integration of Geographic Information Systems. It identifies areas of potential slope failure and factors driving the landslide there. Map layers developed and the lineament used to create a database using the GIS covered factors such as topography (slope, aspect, and curvature), lithology type, soil series, rainfall, drainage, and roads. The production of the slope failure/ landslide zone map based on the ANN’s weightage classifies slope failures into four vulnerability zones, namely, very low, low, medium, and high. Results from this study prove the capability of the GIS-aided ANN model in identifying potential areas of slope failure.