Determination of important topographic factors for landslide mapping analysis using MLP network.
Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.
Imaging and Computational Intelligence (ICI) Group, School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia.
Mutasem Sh
MSh
Alkhasawneh
Imaging and Computational Intelligence (ICI) Group, School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia.
Umi Kalthum
UK
Ngah
Imaging and Computational Intelligence (ICI) Group, School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia.
Lea Tien
LT
Tay
Imaging and Computational Intelligence (ICI) Group, School of Electrical & Electronic Engineering, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia.
Nor Ashidi
NA
Mat Isa
Department of Computer Science, Faculty of Science and Information Technology, Jadara University, Irbid 21110, Jordan.
Mohammad Subhi
MS
Al-batah
D000465:Algorithms; D055876:Landslides; D008296:Malaysia; D008962:Models, Theoretical; D016571:Neural Networks, Computer