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Open AccessArticle

Flood Susceptibility Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia

Department of Urban & Regional Panning, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 32141, Saudi Arabia
Geospatial Analysis and Modelling Research Group, Department of Civil & Environmental Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
College of Architecture and Planning, Imam Abdulrahman Bin Faisal University (formerly, University of Dammam), P.O. Box 1982, Dammam 32141, Saudi Arabia
Architectural Department, College of Architecture, Sudan University of Science and Technology, Khartoum P.O. Box 11111, Sudan
Architectural Department, College of Engineering, Hail University, Hail P.O. Box 2440, Saudi Arabia
Department of Geomatics Engineering Technology, Yanbu Industrial College, Yanbu 41912, Saudi Arabia
Center for Advanced Modeling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia
Department of Energy and Mineral Resources Engineering, Choongmu-gwan, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
Author to whom correspondence should be addressed.
Water 2019, 11(3), 615;
Received: 31 December 2018 / Revised: 6 March 2019 / Accepted: 11 March 2019 / Published: 25 March 2019
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control. View Full-Text
Keywords: analytic network process; GIS; remote sensing; flood susceptibility; Malaysia analytic network process; GIS; remote sensing; flood susceptibility; Malaysia
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Dano, U.L.; Balogun, A.-L.; Matori, A.-N.; Wan Yusouf, K.; Abubakar, I.R.; Said Mohamed, M.A.; Aina, Y.A.; Pradhan, B. Flood Susceptibility Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia. Water 2019, 11, 615.

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