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میثاق, نورالدین, نیسانی سامانی, نجمه, تومانیان, آرا. (1397). شبیه‌سازی رشد شهری تبریز با استفاده از مدل CA-Markov و تصمیم‌گیری چندمعیاره. , 50(1), 217-231. doi: 10.22059/jhgr.2017.224800.1007382
نورالدین میثاق; نجمه نیسانی سامانی; آرا تومانیان. "شبیه‌سازی رشد شهری تبریز با استفاده از مدل CA-Markov و تصمیم‌گیری چندمعیاره". , 50, 1, 1397, 217-231. doi: 10.22059/jhgr.2017.224800.1007382
میثاق, نورالدین, نیسانی سامانی, نجمه, تومانیان, آرا. (1397). 'شبیه‌سازی رشد شهری تبریز با استفاده از مدل CA-Markov و تصمیم‌گیری چندمعیاره', , 50(1), pp. 217-231. doi: 10.22059/jhgr.2017.224800.1007382
میثاق, نورالدین, نیسانی سامانی, نجمه, تومانیان, آرا. شبیه‌سازی رشد شهری تبریز با استفاده از مدل CA-Markov و تصمیم‌گیری چندمعیاره. , 1397; 50(1): 217-231. doi: 10.22059/jhgr.2017.224800.1007382

شبیه‌سازی رشد شهری تبریز با استفاده از مدل CA-Markov و تصمیم‌گیری چندمعیاره

پژوهشهای جغرافیای انسانی
مقاله 14، دوره 50، شماره 1، فروردین 1397، صفحه 217-231    اصل مقاله (1.2 M)
نوع مقاله: مقاله علمی پژوهشی
شناسه دیجیتال (DOI): 10.22059/jhgr.2017.224800.1007382
نویسندگان
نورالدین میثاق1؛ نجمه نیسانی سامانی* 2؛ آرا تومانیان2
1دانشجوی دکتری سنجش‌ازدور و سیستم اطلاعات جغرافیایی دانشکدة جغرافیا، دانشگاه تهران
2استادیار سنجش‌ازدور و سیستم اطلاعات جغرافیایی دانشکدة جغرافیا، دانشگاه تهران
چکیده
امروزه شهرهای کشورهای درحال‌توسعه و توسعه‌یافته، به‌طور هم‌زمان در حال تجربة تغییرات سریع و رشد در مساحت و جمعیت هستند. لازمة مدیریت رشد شهری پایدار و برنامه‌ریزی توسعة شهری، درک الگوهای صحیح رشد شهری است. در این تحقیق سعی شده تا روند گسترش مناطق شهری تبریز با استفاده از تصاویر ماهواره‌ای از سال 1372 تا 1392 برآورد، و نقشة رشد شهری سال 1407 با استفاده از مدل ترکیبی مارکوف- سلول‌های خودکار (CA-Markov) شبیه‌سازی شود. نتایج نشان می‌دهد در این مدت مناطق شهری در سال 1372 از 70 هزار و 90 به 11 هزار و 697 هکتار در سال 1392 افزایش داشته است که 98/64 درصد رشد را نشان می‌دهد، همچنین با استفاده از مدل CA-Markov با دقت کلی 91 درصد می‌توان گفت این افزایش در پانزده سال آینده، یعنی تا سال 1407 نیز ادامه خواهد داشت و با رشد 25 درصدی در مقایسه با سال 1392 به 14 هزار و 690 هکتار خواهد رسید، با توجه به این مسئله نیاز به برنامه‌ریزی مناسب به‌منظور کاهش آسیب‌های ناشی از رشد شهری به دیگر ابعاد شهری احساس می‌شود.
کلیدواژه‌ها
تبریز؛ رشد شهری؛ سنجش‌ازدور؛ CA-Markov؛ AHP
عنوان مقاله [English]
Simulation of Urban Development in Tabriz Using CA-Markov Model and Multi-criteria Decision Making
نویسندگان [English]
Nooroldin Misagh1؛ Najmeh Neysani Samani2؛ Ara Tomanain2
1PhD Student in Remote Sensing and Geographic Information Systems, Faculty of Geography, University of Tehran, Iran
2Assistant Professor of Remote Sensing and Geographic Information Systems, Faculty of Geography, University of Tehran, Iran
چکیده [English]
Introduction
Today, developed and developing countries are experiencing rapid changes and growth in population. It is essential to have a suitable sustainable urban growth management and urban development planning to better understand patterns of urban growth. Satellite remote sensing in conjunction with Geographic Information Systems (GIS) has been recognized as a powerful and effective tool in detecting land use and land cover changes. Satellite remote sensing is a potentially powerful means of monitoring land-use change at high temporal resolution and lower costs than those associated with the use of traditional methods. This provides multi-spectral and multitemporal data that can be used to quantify the type, amount and location of land use and land cover changes. CA-Markov model is a dynamic model to simulate urban growth and land use changes maps obtained from a combination of automated cells and Markov chain. Markov chain is spatial sequence of random processes in which the result of any process at any time, only next time, will depend on the outcome of the process. Using Markov chain model, we have initially calculated the possibility of changing land use map classes to each other in terms of probability matrix applications based on area changes between time t0 and t1. Markov model output, literally, is the non-place model where there is no knowledge of the geographical location of land uses. To predict the location of land at the time t1, automated cell techniques can be used with this model. In this study, we are using Landsat images of TM5 and OLI applying the capabilities of IDRISI software and GIS to estimate changes in urban growth areas in Tabriz during 30 years, from 1973 to 2013.
 
Methodology
In this study, the tools available in IDRISI SELVA software and GIS functions have been used to simulate the changes in land use and urban growth in Tabriz in three main stages:
Tabriz is one of the major cities in Iran and the capital of East Azerbaijan province. The Tabriz City is the the third largest city of Iran following Tehran and Mashhad and it is a major hub for business, communication, commerce, and political, industrial, cultural and military activities.
In this study, in order to identify and create land use maps of Tabriz, images of Landsat in the years 1973, 1993 and 2013 were obtained from the Geological Society of America (USGS).
The land use map of the city of Tabriz has been categorized for three major landuses including urban areas, agricultural land and orchards, and barren areas. In order to make land use suitability map, we have also used topographic maps of 1: 2000 and 1: 50000 for the sheet of Tabriz, from the national cartographic center of Iran. The transition probability matrix is calculated using Markov chain analysis: for this purpose, Landsat satellite images in 1993, 2003 and 2013, using the techniques of USGS classified images to produce the maps of urban development. 

The calculation of urban suitability map using Multi Criteria Evaluation and Analytical Hierarchy Process (AHP)
Urban growth modeling with data collection: 1. urban areas Map 1993 as the base map. 2- Suitability map of urban growth in 2003. 3- The transition probability matrix from 2003 to 1993 was also combined by the operator, CA location. 

 
Results and discussion
The study area, Tabriz city, is located northwest Iran. The maps of land use and urban growth have been created using satellite image processing techniques and supervised classification. The overall accuracy of the land use/cover maps for 1972, 2003 and 2013 were 82 %, 85 % and 90 %, respectively. The Kappa index for the 1972, 1990 and 2006 of the land use/cover maps were found to be 76 %, 79 % and 89 %, respectively. The transfer matrix regions from 2003 to 2013 changed 12 percent of rural areas into urban. Real and simulated map of 2013 is shown in Figure 1. The overall accuracy and Kappa index between actual and predicted maps of 2013 was, respectively, 91 and 81. The 2028 map was produced using ca-markov model. In the map simulated for 2028, urban areas will grow 25 percent and from 11697 hectares to 14690. 
 
Conclusion
In the present study, Markov and CA- Markov models were helpful for predicting land use/cover changes and urban growth in 2013 and 2028. The results showed that the rate of the population growth in the areas built in the city of Tabriz surpassed the value. The gap between urban growth and population doubled in this period and shows that development was more horizontal than vertical during this period. In the map, several areas of industrial, commercial and residential development was found. The outcomes of this research indicate that Landsat TM images can be effectively used for generating accurate land use/cover maps as the overall accuracies of all the generated land cover maps were about 80 %. According to the results of the CA-Markov model, urban expansion will occur in the future. The combination of satellite remote sensing, GIS and Markov models provides useful information on land use/cover dynamics and trends which could help policy makers make better decisions for the future for the study area. The provided future projection could be effectively used for land use planning, decision making and land management, especially if its use is confined more to general trends than to specific land-use locations, where accuracy was lower. The predictive power of the CA-Markov model, especially in predicting the location of pixels, was not very high in this research but, in general, Markov models have indicated the capability for the prediction of land cover/land use trends. 
کلیدواژه‌ها [English]
CA-Markov, AHP, remote sensing, Tabriz, Urban Growth
مراجع
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Statistical Center of Iran., 2011, Report of the Results of the Population and Housing Public Census 2011, Vice Presidential Planning, Tehran

 

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