Urban Development Modeling Using Integrated Fuzzy Systems, Ordered Weighted Averaging (OWA), and Geospatial Techniques

Neda Ghasemkhani, Saeideh Sahebi Vayghan, Arnick Abdollahi, Biswajeet Pradhan and Abdullah Alamri
Additional contact information
Neda Ghasemkhani: Department of Geography and Urban Planning, Islamic Azad University, 1148963537 Tehran, Iran
Saeideh Sahebi Vayghan: Department of Remote Sensing and GIS, Kharazmi University, 1571914911 Tehran, Iran
Arnick Abdollahi: Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia
Biswajeet Pradhan: Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia
Abdullah Alamri: Department of Geology & Geophysics, College of Science, King Saud Univ., P.O. Box 2455, Riyadh 11451, Saudi Arabia

Sustainability, 2020, vol. 12, issue 3, 1-26

Abstract: This paper proposes a model to identify the changing of bare grounds into built-up or developed areas. The model is based on the fuzzy system and the Ordered Weighted Averaging (OWA) methods. The proposed model consists of four main sections, which include physical suitability, accessibility, the neighborhood effect, and a calculation of the overall suitability. In the first two parts, physical suitability and accessibility were obtained by defining fuzzy inference systems and applying the required map data associated with each section. However, in order to calculate the neighborhood effect, we used an enrichment factor method and a hybrid method consisting of the enrichment factor with the Few, Half, Most, and Majority quantifiers of the ordered weighted averaging (OWA) method. Finally, the three maps of physical suitability, accessibility, and the neighborhood effect were integrated by the fuzzy system method and the quantifiers of OWA to obtain the overall suitability maps. Then, the areas with high suitability were selected from the overall suitability map to be changed from bare ground into built-up areas. For this purpose, the proposed model was implemented and calibrated in the first period (2004–2010) and was evaluated by being applied to the second period (2010–2016). By comparing the estimated map of changes to the reference data and after the formation of the error matrix, it was determined that the OWA-Majority method has the best estimation compared to those of the other methods. Finally, the total accuracy and the Kappa coefficient for the OWA-Majority method in the second period were 98.98% and 98.98%, respectively, indicating this method’s high accuracy in predicting changes. In addition, the results were compared with those of other studies, which showed the effectiveness of the suggested method for urban development modeling.

Keywords: fuzzy inference system; GIS; ordered weighted averaging (OWA); physical suitability; accessibility suitability; urban development prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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