Abstract
Urban sprawl has become a very complex process, because it has many factors affecting its directions and values. The study of relative research shows that the driving forces that lead and redirect future urban sprawl require the application of a statistical method. In our study, logistic regressions were used to analyze and class the driving forces for urban sprawl. Identifying the driving forces, which is the most important step in predicting the future of urban sprawl in 2037, was performed using the cellular automata models. This study takes the Aswan area as a case study in the period from 2001 to 2013 by analyzing the official detailed plan and Google Earth historical imagery. Almost all data was prepared for logistic regression analysis using ArcGIS software and IDRISI® Selva. In our study, a hybrid model of the Markov chain and logistic regression models was applied to identify future urban sprawl in 2037. The findings of this paper simulate the increase in urban area over 24 years from 1.85 to 2.59 km2. These findings highlight the growing risks of urban sprawl and the difficulties opposing the sustainable urban development plans officially proposed for this area.
Highlights
According to United Nations projections, it is forecasted that global urban land will increase by1.2 million km2 by 2030, which will be almost triple the global urban land area circa 2000 [1]
We could not conduct a proper analysis of the files, provided free of charge, online, for example, the Digital elevation models (DEMs) files
We could not conduct a proper analysis of the urban buildings inDigital the urban areas were (DEMs)
Summary
According to United Nations projections, it is forecasted that global urban land will increase by1.2 million km by 2030, which will be almost triple the global urban land area circa 2000 [1]. According to United Nations projections, it is forecasted that global urban land will increase by. Besides increasing traffic volume, caused by this urban structure, the consumption of natural resources is advocated and biodiversity is lost, among other negative impacts [2]. To counteract such development tendencies and to ensure sustainability, decision-makers and urban planners need precise information on urban expansion boundaries [3]. Since the speed of development in emerging countries is higher than that in the developed world [5], the structural changes facing these countries have a greater impact on the urban fabric [6].
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