Scientific- Research Quarterly of Geographical Data (SEPEHR)

Scientific- Research Quarterly of Geographical Data (SEPEHR)

Urban expansion modeling using medium resolution satellite imagery based on cellular automata (Case study: Tehran city)

Document Type : Research Paper

Authors
Amir Hossein Kazem 1
Farhad Hosseinali 2
Ali Asghar Ale-sheikh 3
1 Student of master in RS & GIS, Azad University sciences and researches branch
2 Assistant professor in GIS, Shahid Rajaei University
3 Professor of GIS, Khaje Nasir University
10.22131/sepehr.2015.14476
Abstract
Modeling urban growth and land use changes are an integral part of planning for sustainable development. The present research intends to model the urban growth and development for Tehran metropolis from the aspect of timeand spatial distribution. To this end, land-use maps for the years 1988, 2002 and 2013 were categorized with the object-based approach using Landsat satellite time series images. In the next step, using the logistic regression model, the effect of independent variables in relation to urban growth including 14 variables in the form of two groups of environmental-natural and socio-economic variables during the period of 1988 to 2002 was calculated as the coefficient in the regression equation, and the potential map of urban expansion was produced. The evaluation of the logistic regression function using two Pseudo R2 and ROC indexes with values ​​of 0.32 and 0.89 showed good regression fit and proper description capability. Subsequently, the area of ​​change for the expected year was quantitatively predicted using Markov chain analysis.Finally, by using the outputs of the two models of logistic regression and Markov chain analysis and using the Cellular Automata Model, urban growth was modeled for the year 2013, comparison of which with the 2013 classified image, shows that the used model with a 93% relative accuracy for the estimated area and a Kappa coefficient of 0.87 has been a successful model. Accordingly, the same model was used to estimate the urban growth in 2025,using images from the years of 2002 and 2013.
Keywords
Modeling Urban Growth
Cellular automata
Object-based classification
Tehran
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