4.6 Article

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

Journal

SUSTAINABILITY
Volume 12, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/su12030809

Keywords

fuzzy inference system; GIS; ordered weighted averaging (OWA); physical suitability; accessibility suitability; urban development prediction

Funding

  1. Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney [323930, 321740.2232335, 321740.2232424, 321740.2232357]
  2. King Saud University, Riyadh, Saudi Arabia [RSP-2019/14]

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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.

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