Evaluating urban sprawl using remote sensing and geographic information systems techniques

Abstract

Urban sprawl and climate change are two main environmental problems of the 21st century, and these two aspects are interconnected. The objectives of this study are to; (i) investigate the process of urban sprawl in Shiraz city, Iran, (ii) describe the history of city growth and to predict the growth using Cellular Automata (CA) environmentally protected scenarios, and (iii) analyze the environmental impact of the past and future urban growth. Urban sprawl of Shiraz city, located in southern part of Iran, in the last 30 years has been measured using multi temporal Landsat and SPOT satellite images taken from four different years; 1976, 1990, 2000 and 2005. Shannon’s entropy method has been used to measure the urban sprawl and the results showed that Shiraz city is in the early stages of sprawl. A Cellular Automata model which is integrated with Markov chain analysis is used to predict the future city growth pattern for the years 2010, 2015 and 2020 by three different designed scenarios. The first scenario takes into account the current growth pattern for the future years, while, the second and the third scenarios have different environmental protection considerations for prediction. The results showed the abilities of CA-Markov based models for city growth simulation. Impacts of urban sprawl on vegetation coverage and water resources for the previous and projected years have been quantified. The results showed that during the past three decades, vegetation coverage and surface water resources in many places have been replaced by the built-up area. It showed that during the past three decades, there was no environmental protection planning over Shiraz city and if the current growth pattern continues in the future, the city will encounter serious environmental problems.