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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Institute of Geography, Faculty of Geography, University of Tehran</PublisherName>
				<JournalTitle>Geographical Urban Planning Research (GUPR)</JournalTitle>
				<Issn>2383-1456</Issn>
				<Volume>7</Volume>
				<Issue>3</Issue>
				<PubDate PubStatus="epublish">
					<Year>2019</Year>
					<Month>09</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Application of Scenario Based SLEUTH Model for Urban Growth Simulation (Case Study: Tabriz Metropolitan Area)</ArticleTitle>
<VernacularTitle>Application of Scenario Based SLEUTH Model for Urban Growth Simulation (Case Study: Tabriz Metropolitan Area)</VernacularTitle>
			<FirstPage>553</FirstPage>
			<LastPage>580</LastPage>
			<ELocationID EIdType="pii">74684</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jurbangeo.2019.279136.1085</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Hassan</FirstName>
					<LastName>Mahmoudzadeh</LastName>
<Affiliation>Associate Professor of Geography and Urban Planning, Department of Geography and Urban Planning, Faculty of Planning and   Environmental Sciences, University of Tabriz, Tabriz, Iran</Affiliation>
<Identifier Source="ORCID">0000-0001-5465-1114</Identifier>

</Author>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Vahedi Aghjea</LastName>
<Affiliation>MSc of Urban and Rural Studies, Department of RS &amp; GIS, Faculty of  Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mahdi</FirstName>
					<LastName>Herischian</LastName>
<Affiliation>PhD Student of Geography and Urban Planning, Department of Geography and Urban Planning, Faculty of Planning and   Environmental Sciences, University of Tabriz, Tabriz, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-1337-3581</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2019</Year>
					<Month>04</Month>
					<Day>12</Day>
				</PubDate>
			</History>
		<Abstract>Introduction   
In recent decades, more than half of the world population have settled in cities, and ongoing increase of the population has led to the physical urban expansion and losing of environmental resources of the earth planet. The physical development of cities has unpleasant effects on the urban environment, and continuing of this non-ecological development trend can be catastrophic for the citizens of vast metropolitan areas. In developing countries, like Iran, over the last two decades, vast areas of natural recourses and biodiversity capacity have has disappeared by uncontrolled development of metropolis. This led to adverse changes such as environmental pollution, biodiversity reduction, and urban marginalization. Therefore urban development must be evaluated using suitable models to avoid environment quality decreasing, land resources, and ecosystems. The Present study aims is to investigate Tabriz metropolis urban growth modeling in the three past decades and to forecast new urban growth trends.
Methodology
This research from the methodology aspect is the descriptive-analytic and categorized in the development - applied type and required information was collected using digital and analog data and field surveys observations.
Sleuth model in Cygwin environment was applied in this study to model urban growth of the Tabriz metropolis. This research used the following materials and software.
Topographic maps in the scale 1/50000 (received from national cartographic center)
Image processing software:
IDRISI Selva
ERDAS IMAGINE
ENVI
Processing of Landsat satellite images (downloaded from USGS website) to perform the following operations:
-Preprocessing of satellite data including Landsat image radiometric correction, image mosaic, image subset…
-Image processing and extraction of land use map
- Survey of urban area changes in the study area in the 1984-2016 period.
Results and discussion
The variables used in this study are including slope, transportation system, land use; exclusion acquired using Landsat satellite images. The Sleuth Urban Growth Model was calibrated for historical data generated from Landsat satellite imagery for the years 1993-2016 in three phases, and the growth coefficients generated by OSM Program were generated Program for next steps. The five urban growth coefficients&#039; values for dispersion, breed, spread, and slope; road gravity was 26, 40, 38, 76, and 89 in 2016 respectively. The acquired coefficients indicated that according to historical data, urban growth was more affected by road gravity factor compared to other cities where slope resistance has little effect on urban development; the topography is an essential factor in the limitation of urban development of Tabriz. Future urban growth trends were predicted by 2040 by designing three scenarios that are historical, mild strict environmental and high stringent Environmental scenarios for Tabriz metropolis.
Conclusion
The results show that if the urban growth continues unplanned by 2040, the growth will occur about 15.5 percent in the region. This study demonstrates the success of the Sleuth model in the calculating of calibration Coefficient at Tabriz using OSM based on historical data from 1993-2016. The coefficients extracted from the calibration process are comparable to the values of other research coefficients based on the Sleuth model. Historical growth scenario has shown that urban development is not limited. From 2016 to 2040, the city will grow by approximately 15.5 percent; in other words, 3241 hectares will be added to Tabriz urban land. This scenario shows the highest increase in urban development, which would result in the loss of large amounts of the natural resource.
The temperate environmental scenario showed the lowest increase compared to the first scenario, which resulted in 1751 hectares of natural resources conservation and indicating an increase of 7.7% in the urban area. According to the predictions made in this study, the metropolitan will develop by about 0 percent under the strict Environmental scenario, and not only conserve much more natural resources than the second scenario but also lead to compact urbanization that facilitates service-level capacity for urban managers. Based on the findings, the second scenario is more suitable and preferable to Tabriz urban development trend than the first and third scenarios. The values of the appropriate coefficients obtained for each indicator of the model show the effectiveness of the sleuth model for predicting urban growth and produced three scenarios is useful for evaluating the consequences of future urban growth. These scenarios provide different growth strategies for planners. The historical growth scenario shows that there is no limit to the development of the city, and Tabriz will have expanded by around 15.5 percent from 2016 to 2040. Among these three scenarios, the second scenario offers with the highest level of environmental protection and provides a small increase for urban land development relatively, which is the most desired result for urban development of Tabriz metropolis. Overall, the use of practical factors in modeling urban development indicates that Tabriz&#039;s urban growth process has been inappropriate due to the loss of valuable lands such as high-quality gardens and lands.
The Sleuth model showed the urban growth characteristics in the Tabriz metropolis and could predict future urban development. The model seems to have a strong potential in urban planning research, enabling municipal managers to understand the nature of urban development and make necessary restrictions for distinct areas, as well as to determine their reactions in a various urban future growth scenario.  The findings also showed that the use of GIS is essential for preparing input data, model calibration, and growth impact assessment, and there is a useful link between GIS and CA in implementing the Sleuth model. The model is also used as a support tool for urban managers to realize the consequences of possible actions.</Abstract>
			<OtherAbstract Language="FA">Introduction   
In recent decades, more than half of the world population have settled in cities, and ongoing increase of the population has led to the physical urban expansion and losing of environmental resources of the earth planet. The physical development of cities has unpleasant effects on the urban environment, and continuing of this non-ecological development trend can be catastrophic for the citizens of vast metropolitan areas. In developing countries, like Iran, over the last two decades, vast areas of natural recourses and biodiversity capacity have has disappeared by uncontrolled development of metropolis. This led to adverse changes such as environmental pollution, biodiversity reduction, and urban marginalization. Therefore urban development must be evaluated using suitable models to avoid environment quality decreasing, land resources, and ecosystems. The Present study aims is to investigate Tabriz metropolis urban growth modeling in the three past decades and to forecast new urban growth trends.
Methodology
This research from the methodology aspect is the descriptive-analytic and categorized in the development - applied type and required information was collected using digital and analog data and field surveys observations.
Sleuth model in Cygwin environment was applied in this study to model urban growth of the Tabriz metropolis. This research used the following materials and software.
Topographic maps in the scale 1/50000 (received from national cartographic center)
Image processing software:
IDRISI Selva
ERDAS IMAGINE
ENVI
Processing of Landsat satellite images (downloaded from USGS website) to perform the following operations:
-Preprocessing of satellite data including Landsat image radiometric correction, image mosaic, image subset…
-Image processing and extraction of land use map
- Survey of urban area changes in the study area in the 1984-2016 period.
Results and discussion
The variables used in this study are including slope, transportation system, land use; exclusion acquired using Landsat satellite images. The Sleuth Urban Growth Model was calibrated for historical data generated from Landsat satellite imagery for the years 1993-2016 in three phases, and the growth coefficients generated by OSM Program were generated Program for next steps. The five urban growth coefficients&#039; values for dispersion, breed, spread, and slope; road gravity was 26, 40, 38, 76, and 89 in 2016 respectively. The acquired coefficients indicated that according to historical data, urban growth was more affected by road gravity factor compared to other cities where slope resistance has little effect on urban development; the topography is an essential factor in the limitation of urban development of Tabriz. Future urban growth trends were predicted by 2040 by designing three scenarios that are historical, mild strict environmental and high stringent Environmental scenarios for Tabriz metropolis.
Conclusion
The results show that if the urban growth continues unplanned by 2040, the growth will occur about 15.5 percent in the region. This study demonstrates the success of the Sleuth model in the calculating of calibration Coefficient at Tabriz using OSM based on historical data from 1993-2016. The coefficients extracted from the calibration process are comparable to the values of other research coefficients based on the Sleuth model. Historical growth scenario has shown that urban development is not limited. From 2016 to 2040, the city will grow by approximately 15.5 percent; in other words, 3241 hectares will be added to Tabriz urban land. This scenario shows the highest increase in urban development, which would result in the loss of large amounts of the natural resource.
The temperate environmental scenario showed the lowest increase compared to the first scenario, which resulted in 1751 hectares of natural resources conservation and indicating an increase of 7.7% in the urban area. According to the predictions made in this study, the metropolitan will develop by about 0 percent under the strict Environmental scenario, and not only conserve much more natural resources than the second scenario but also lead to compact urbanization that facilitates service-level capacity for urban managers. Based on the findings, the second scenario is more suitable and preferable to Tabriz urban development trend than the first and third scenarios. The values of the appropriate coefficients obtained for each indicator of the model show the effectiveness of the sleuth model for predicting urban growth and produced three scenarios is useful for evaluating the consequences of future urban growth. These scenarios provide different growth strategies for planners. The historical growth scenario shows that there is no limit to the development of the city, and Tabriz will have expanded by around 15.5 percent from 2016 to 2040. Among these three scenarios, the second scenario offers with the highest level of environmental protection and provides a small increase for urban land development relatively, which is the most desired result for urban development of Tabriz metropolis. Overall, the use of practical factors in modeling urban development indicates that Tabriz&#039;s urban growth process has been inappropriate due to the loss of valuable lands such as high-quality gardens and lands.
The Sleuth model showed the urban growth characteristics in the Tabriz metropolis and could predict future urban development. The model seems to have a strong potential in urban planning research, enabling municipal managers to understand the nature of urban development and make necessary restrictions for distinct areas, as well as to determine their reactions in a various urban future growth scenario.  The findings also showed that the use of GIS is essential for preparing input data, model calibration, and growth impact assessment, and there is a useful link between GIS and CA in implementing the Sleuth model. The model is also used as a support tool for urban managers to realize the consequences of possible actions.</OtherAbstract>
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