Volume 26, Issue 2 (12-2016)                   IJAUP 2016, 26(2): 161-172 | Back to browse issues page

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Abedini A, Azizi P. Prediction of future urban growth scenarios using SLEUTH model (Case study: Urmia city, Iran). IJAUP. 2016; 26 (2) :161-172
URL: http://ijaup.iust.ac.ir/article-1-278-en.html
Abstract:   (6059 Views)

Rapidly increasing urbanization in the world, especially in developing countries, let to increasing urban extents. Rapid urban growth causes to appearance many problems such as wasting environmental resources, inability of providing necessary services for citizens and unplanned growth. Urban mangers and planners need tools for understanding amount and size of future urban growths to prevent these problems. Urmia as capital city of west Azerbaijan province, in the last decades has considerable growth in both extent and population. This rapid growth caused to lose most high value agricultural resources in its surrounding. It has also caused many problems for urban management. Therefore, how city managers and urban planners can be aware of magnitude and location of Urmia city’s future growth and what is the best growth scenario for Urmia city? This paper uses a quantitative analysis research methodology to prediction and evaluation of growth scenarios for Urmia city. In this paper, SLEUTH model was applied to predict future urban growth of Urmia until 2050. Two different scenarios were employed include: Historical Growth Scenario (HGS) and Environment Protection Scenario (EPS). The result highlight that if the city continues its growth based on HGS scenario, in compare with growth based on EPS scenario, it would occupy more area. In this paper, we concluded that the EPS scenario can be more sufficient than HGS scenario. In addition, SLEUTH urban growth model can be used as a planning support model for urban planners and managers decisions for Urmia city based on scenarios.

Full-Text [PDF 1092 kb]   (1935 Downloads)    
Type of Study: Research Paper | Subject: Urban Planning
Received: 2015/11/28 | Accepted: 2016/12/31 | Published: 2016/12/31

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