On the Evaluation of Factors Affecting Urban Growth by Emphasizing on Land Use Changes by Means of Using a Logistic Regression Model (Case Study: Tabriz City)

Subject Areas : Urban and Regional Planning Studies

rahim  sarvar ¹ (استاد گروه جغرافیا و برنامه ریزی شهری، واحد علوم تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران)
rasool  yazdani ² (دانشجوی دکتری جغرافیا و برنامه ریزی شهری، دانشگاه تبریز، تبریز، ایران)
ali  eshghi chaharborj ³ (دانشجوی دکتری جغرافیا و برنامه ریزی شهری، دانشگاه محقق اردبیلی، اردبیل، ایران)

Received: 2015-10-26 Accepted : 2016-12-03 Published : 2016-11-21

Keywords: physical development, Tabriz, effective indicators of urban growth, the logistic regression model,

Abstract :

Horizontal and unplanned expansion of cities by population growth and migration, leading to, Shortage of land, the land adjacent to urban constructions and the creation of slums in places has a natural disadvantage. Tabriz city in recent decades has experienced rapid growth and physical development. Uncontrolled urban growth, land degradation desirable garden surrounding cities, the creation of slums in steep areas on the Tabriz fault, traffic and pollution has been. Management and planning for urban growth and reduce the adverse effects of changes in land use and urban growth factors is necessary. In the present study logistic regression model, as a high capacity data-driven model has many variables involved To analyze the development of the city and the relationship between urban growth patterns and the factors driving it is being used . This research is descriptive analytic functional purpose. In this study, using the classification of satellite images over a 22 year period (1989-2011) Using maximum likelihood method changes cover/land Tabriz and surrounding lands were discovered and analyzed. The 14 independent variables and the dependent variable factors driving urban growth or urban development has taken place over the last 22 years were tested. The modeling was done for the period 2011 and 2033. Using data from 1989 to 2011 was modeled urban growth Consistent output over the map in 2011 with the actual land use map of 2011 confirmed the accuracy of the modeling contract. Finally, growth in 2033 was modeled to show results The possibility of development in the South East or North West of Tehran road (towards Marand and Bazargan border) and South West (towards Azarshahr) is the more than. To validate the modeling and understanding the factors that influence urban growth ROC method was used The results of the effects of the distance from the gardens and urban land And then factors in the development of arid lands and gardens is over 22 years.

References:

Achmad, A., Hasyim, S., Dahlan, B., & AuliaDwira, N. )2015(. Modeling of urban growth in tsunami-prone city using logistic regression: Analysis of Banda Aceh. Indonesia, Applied geography, )62(, 237-246.

Ahadnejad Roshti, M. (2001). assessment and modeling of land use change using multi-temporal imagery and geographic information system (Maragheh study area). Snjshazdvr graduate thesis, Tarbiat Modarres University, 102. (in persian)

Alsharif, A., & Pradhan, B. )2014(. Urban sprawl analysis of Tripoli metropolitan city (Libya) using remote sensing data and multivariate logistic regression model. Journal of Indian society of remote sensing, 42 (1), 155-170.

Bounoua, L., Safia, A., Masek, J., Peters-Lidard, C., & Imhoff Marc, L. )2009(. Impact of urban growth on surface climate: a case study in Oran. Algeria. Journal of applied meteorology and climatology, 48, 218-231.

Deep, Sh., & Saklani, A. )2014(. Urban sprawl modeling using cellular automata. The Egyptian journal of remote sensing and space sciences, 17, 179-218.

Department of Urban Planning and Architecture of the City of Tabriz. (2014). the most important rules and regulations detailed plan of Tabriz. (in persian)

ESA-UN. )2007(. World Urbanization Prospects. The 2005 Revision.2

Fang, S., Z Gertner, G., Sun Z., & A. Anderson, A. )2005). the impact of interactions in spatial simulation of the dynamics of urban sprawl. Landscape and urban planning, 73, 294- 306.

Gong, P. (1993). Change Detection Using Principal Component Analysis and Fuzzy Set Theory. Can, J. Remote Sensing. 19(1) 22 - 29.

Gorbany, R., PourMohammadi, M., Mahmoud Zadeh, H. (2015). the environmental approach in modeling land use changes Tabriz metropolitan area using satellite images several times, multi-criteria assessment and automated cells Markov chain (from 1984 to 2038). Journal of urban studies, 8, 13-30. (in persian)

Han, J., Hayashi, Y., Cao, X., & Imura, H. (2009). Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai. China Landscape and Urban Planning. www.elsevier.com.

Hu, Zhiyong., & Lo, C.P. (2007). Modeling urban growth in Atlanta using logistic regression, Computers. Environment and urban systems, 31, 667-688.

Jenerette, G.D., & Wu, J. (2001). Analysis and simulation of land use change in the central Arizon Phoenix region, USA. Landscape Ecology, 16, 611-626.

JokarArsanjani, J., Helbich, M., Kainz, W., & DarvishiBloorani, A. (2012). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International journal of applied earth observation and geoinformation. (in persian)

Kamyab, H.R., Salman Mahiny, A., Hosseini, S.M., & Gholamalifard, M. (2010). Adopted a data-driven approach using logistic regression modeling Gorgan Urban Development. Ecology Journal, 54, 89-96. (in persian)

Lopez, E., Bocco, G., Mendoza, M., & Duhau, E. (2001). Predicting land-cover and land-use change in the urban fringe, a case in Morelia city, Mexico. Landscape and urban planning, (55), 271-285.

Mashhadizadeh Dehaghani, N. (1995). An analysis of the characteristics of urban planning at Iran University of Science and Technology. Tehran. (in persian)

Mishra, M., Mishra, K.K., & Subudhi, A. P. (2014). Urban sprawl mapping and land use change analysis using remote sensing and GIS (Case study of Bhubaneswar City, Orissa). Retrieved from www.gisresources.com.

Momany, I. (2011). Urban growth modeling in Tehran in 2050 using the model SLEUTH. Centre for Studies and Planning in Tehran, Tehran Municipality. (in persian)

Opulation Division, United Nations. (2009). World population prospects. UN.

Park, S., Jeon, S., Kim, S. & Choi, C. (2011). Prediction and comparison of urban growth by land suitability index mapping using GIS and RS in South Korea. Landscape and urban planning, 99 (2), 104-114.

PourMohammadi, M. R., Jamali, F., & Zamani, A. (2008). To evaluate the spatial expansion of the city _Kalbdy with an emphasis
 on changes in land use over the period 1976 to 2005. Geographical Research, 63, 46-29.(in persian)

Rabii, H.R., Ziaeian, P., Ali Mohammadi, A. (2006). Discovery and recovery of the city land use changes and land cover of the remote sensing and geographic information systems. human science teachers Quarterly, 9 (4), 19 -32. (in persian)

Rafiee, R., Salman Mahiny, A., Khorasani, N., Darvishsefat. A.A., & Danekar, A. (2009). simulating urban growth in Mashad city, Iran through the SLEUTH model (UGM). Cities, 26, 19-26.

Rafiee, R., Salman Mahiny, A., Khorasani, N., Darvishsefat. A.A., & Danekar, A. (2009).  simulating urban growth in Mashad city, Iran through the SLEUTH model (UGM). Cities, 26, 19-26.(in persian)

Rostaiy, sh., Ahadnejad, M., & farokhi suma, M. (2015). Assess the extent of the urban space with an emphasis on land use changes using multi-temporal satellite images (Case Study: Orumiyeh). Journal of Geography and Planning, 18 (50), 189-2006. (in persian)

Statistical Center of Iran, in 2011, General Population and Housing Census. The city of Tabriz.(in persian)

Sun, C., Zhi-feng, W., Zhi-qiang, L., Na, Y., & Jian-bing, W. (2013). Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 21, 409-417.

Thapa, B.R., & Murayama, Y. (2010). Drivers of urban growth in the Kathmandu valley, Nepal: Examining the efficacy of the analytic hierarchy process. Applied Geography, 30 (1), 70-83.

The role of Consulting Engineers Environment. (2013). development plan (comprehensive) in Tabriz.(in persian)

United Nations, Department of economic and social affairs. (2010). World urbanization prospects: The 2010 revision, New York: United nation publication.

United Nations, Department of economic and social affairs. (2014). World urbanization prospects: The 2014 revision, New York: United nation publication.

Vahedian Beigy, L., Pourahmad, A., & Syfaldyny, F. (2012). The effects of land use change Tehran's District 5. New Perspectives in Human Geography Journal, 4 (1), 29-46. (in persian)

Vermeiren, K., Van, R. A., Loopmans, M., Serwajja, Eria., & Mukwaya, P. (2012). Urban growth of Kampala, Uganda: Pattern analysis and scenario development. Landscape and urban planning, 106, 199-206.

Wakode, H. B., Klaus, B., Ramakar, J., & Raffig, A. (2014). Analysis of urban growth using Lands at TM/ETM data and GIS- a case study of Hyderabad, India. Arabian Journal of Geosciences, 7 (1), 109-121.

Zhao, P., (2011). Managing urban growth in a transforming China: Evidence from Beijing. Land Use Policy, www.elsevier.com.