Evaluating urban growth trends by using SLEUTH model:a case study in Adana

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2019
Çapan, Hüseyi
In this study, various urban growth scenarios are simulated for Adana city by using SLEUTH urban growth model. In addition, the impact of the planned road in 2020 was investigated. The results of this study were compared with other SLEUTH model applications using a SLEUTH-specific comparison method. SLEUTH is a cellular automata simulation model developed for urban growth modelling. It is written in the C language and has an open source library. Since its first occurrence as an urban growth model, SLEUTH model has become the most popular one. It has been applied to more than 50 cities, with various scales, around the world. Superiority of the SLEUTH against other cellular automata approaches has been proven in some studies in the literature. Adana has the most fertile lands in Turkey, but it has been facing with immigration and rapid urbanization problems. Landsat imagery acquired in 1990, 2001, 2006, 2011 and 2016 for Adana are used as input dataset for the SLEUTH model. Urban plan for 2016 has been obtained from official sources in order to create a basis for the scenarios. Urbanization in 2050 is estimated using three scenarios representing current trends, and green areas being fully and partially v protected. Model sensitivity has been discussed and the changes in the impervious surfaces in the area are obtained. Prediction results show that the model responds each scenario in a different manner. Between 2016 and 2050 percent urban area increase for the first scenario is 120%, for the second scenario it is 62% and for the last and most protective third scenario, 50% increase in urban areas have been predicted. Detailed urbanization analyses have been performed to find green and agricultural area losses due to urbanization in the future
Citation Formats
H. Çapan, “Evaluating urban growth trends by using SLEUTH model:a case study in Adana,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Geodetic and Geographical Information Technologies., 2019.