University of Tabriz Journal of Geography and Planning 2008-8078 20 58 2017 02 08 Modeling Urban Development Using Fuzzy-Cellular Automata Modeling Urban Development Using Fuzzy-Cellular Automata 159 179 5810 2 FA Mohammad Taleai Associate Professor in Faculty of Geodesy & Geomatics, K.N.Toosi University of Technology, Tehran, Iran. Meysam Aghamohammadi M.S degree of Geographical information systems (GIS), faculty of Geodesy & Geomatics, K.N.Toosi University of Technology, Tehran, Iran. Mohammad Karimi Assistance Professor in Faculty of Geodesy & Geomatics, K.N.Toosi University of Technology, Tehran, Iran Ghasem Javadi Faculty Member of Geomatics Eng., University of Bojnord, P. O. Box 1339, Bojnord 94531, Iran. Journal Article 2014 04 29 Rapid, irregular and unbalanced growth of the world population during past years, particularly in developing countries, have been caused many problems in the areas of environmental, economic, social and cultural for urban planners. These situations request new methods and tools to model and predict urban future changes. Due to simple and dynamic structure and utilizing spatial characteristics, Cellular Automation (CA) model widely uses in spatial-temporal modeling problems such as urban extension. This paper develops a Fuzzy-CA method to model urban extension. In conventional CA method, state and position of pixels and transition rules are defined certainly. The definitive expression of components of the complex processes needs a large amount of data. However in most cases accurate data are not available. As a result, integration of CA method and fuzzy theory would be useful to model urban extension. In this paper a Fuzzy-CA method is developed and tested in Shiraz city between the years 2004 to 2009. The results of the proposed method show 80% accuracy in comparison to real data have been captured from satellite images. However, an accuracy of 75% has been reported for this case study with utilizing conventional cellular automation. Rapid, irregular and unbalanced growth of the world population during past years, particularly in developing countries, have been caused many problems in the areas of environmental, economic, social and cultural for urban planners. These situations request new methods and tools to model and predict urban future changes. Due to simple and dynamic structure and utilizing spatial characteristics, Cellular Automation (CA) model widely uses in spatial-temporal modeling problems such as urban extension. This paper develops a Fuzzy-CA method to model urban extension. In conventional CA method, state and position of pixels and transition rules are defined certainly. The definitive expression of components of the complex processes needs a large amount of data. However in most cases accurate data are not available. As a result, integration of CA method and fuzzy theory would be useful to model urban extension. In this paper a Fuzzy-CA method is developed and tested in Shiraz city between the years 2004 to 2009. The results of the proposed method show 80% accuracy in comparison to real data have been captured from satellite images. However, an accuracy of 75% has been reported for this case study with utilizing conventional cellular automation. https://geoplanning.tabrizu.ac.ir/article_5810_7faa1d02a235adef06ab435b99aa7b06.pdf