AbstractIrregular growth in the surrounding lands is one of the most important issues for the city managers and programmers at various levels. Whereas nowadays study the process of land use changes to urban use plays the main role in long time decisions and programs, predicting the process of city growth and its modeling in future with precise methods for management and urban expansion control will be necessary more than other times. One of urban growth modeling is cellular automata model. This model has been used widely in urban studies because of its dynamic nature, ability of Integration with other models, ability to modify the model and required data availability. In this article, to maximize the efficiency of the cellular automata model and its constraints, the integration of the AHP automated cell model and cellular automata model have been used; and its accuracy has been evaluated. This article has been practical because its related principles has been collected in a documentary manner and has been used to analyses the issue in comparative and quantitative methods. Initially, the unplanned growth of Qazvin city has been investigated by Holdern and Shannon model. Then main parameters including distance from roads, land prices, distance from faults, distance from the rivers, soil gender, slope, permission to build land, topography, landscape, view to gardens and forest park as parameters involved in the development of Qazvin city are considered. The input data used in this research are Landsat tm and DEM images of the city of Qazvin in 1996 and 2016. Also, to evaluate the correctness of the model responses, the map of the developed regions in 2016 and the Kappa coefficient have been used. The Kappa coefficient is 92.3%, which is considered significant and appropriate and gave the fact that the Kappa number is acceptable. The Qazvin simulation was made in 2026. The results show that the proposed integrated model is suitable for studying urban growth.
Comparison of Urban Growth Modeling Using Deep Belief and Neural Network Based Cellular Automata Model—A Case Study of Chennai Metropolitan Area, Tamil Nadu, India
