Simulation of the Spatial Pattern of Land Use Change in the City of Gachsaran Using Cellular Automata Model
Subject Areas : Architecture and urbanismMohsen Derakhsh 1 , Soheil Sobhan Ardakani 2
1 - Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran
2 - Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran
Keywords: Gachsaran, Kappa coefficient, Urban development, land use, Automata cellular model,
Abstract :
Background and Objective: Simulation of land-use change is very useful for governmental plans and policies. A number of models including system models, Markov chains, the CLUES-S and the SLEUTH have been developed for the simulation of land-use change. Among them, cellular automata (CA) modeling is widely applied to simulate complicated dynamic systems. In this regard, information on land use and also land cover and possibilities for their optimal use is essential for the selection, planning and implementation of land use schemes to meet the increasing demands for basic human needs and welfare.Therefore, this study was conducted to forecasting and modeling of urban development of city of Gachsaran using a CA Model for 2044. Method: In this descriptive study, the land use mapping, a predominantly cloud-free image of Landsat Multispectral Scanner (MSS, 1972), Landsat Thematic Mapper (TM, 1986), Landsat Enhanced Thematic Mapper (ETM+, 1999), and Operational Land Imager (OLI, 2015) were used to the modeling of land-use changes of the study area between the periods 1972 to 2015, and also to the simulation of land-use changes of city of Gachsaran in 2044. Findings: Based on the results obtained, the increasing growth of urban use over time, particularly in the northern part of the city, and the decline in natural and ecological land use, especially agricultural land were observed. Also, the results clearly suggest that the development process of the city of Gachsaran during the recent years did not follow a proper pattern and, especially the unbalanced growth could be observed in the western part of the city. On the other hand, according to the forecasting of model output, in 2044 about 70% of the extent of the study area, will be dedicated to urban use. Discussion and Conclusion: In general, it can be admitted that the CA model has a high ability in simulating the urban development process and can effectively be used to study the urban dynamic, especially in rapidly growing cities.
4- He, Ch., Okada, N., Zhang, Q., Shi, P., Li, J. 2008. Modelling dynamic urban expansion processes incorporating a potential model with cellular automata. Landscape and Urban Planning, 86(1): 79-91.
11- Dadashpoor, H., Jahanzad, N. 2015. Simulation of future land use changes based on an ecological optimal pattern in Mashhad Metropolitan area. Geographical Urban Planning Research, 3(3): 343-359. (In Persian)
12- Maboodi, M.T., Hakimi, H. 2015. Analysis of land use changes and urban sprawl simulation in mid-sized cities (Case study: Khoy City). Geographical Urban Planning Research, 3(2): 211-226. (In Persian)
16- Jokar Arsanjani, J., Helbich, M., Kainz, W., Darvishi Boloorani, A. 2013. Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21: 265-275.
18- Poor Ahmad, A., Ziari, K.A., Mohammadi, R. Spatial distribution pattern of urban uses in oil-rich cities (Case study: Dogonbadan city). Geographical Research, 25: 21-50. (In Persian)
19- Bali, A., Monavari, S.M., Jafari, M., Abdolahi, Sh. 2012. Land uses change patterns in Anzali Wetland basin during 2000, 1989, 1975 and 2007 with emphasis on urban development and constructed lands. Journal of Environmental Science and Bioengineering, 53-54: 73-80. (In Persian)
20- Eerens, H., Haesen, D., Rembold, F., Urbano, F., Tote, C., Bydekerke, L. 2014. Image time series processing for agriculture monitoring. Environmental Modelling & Software, 53: 154-162.
21- Butt, A., Shabbir, R., Ahmad, S.S., Aziz, N. 2015. Land use change mapping and analysis using Remote Sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan. The Egyptian Journal of Remote Sensing and Space Science, 18(2): 251-259.
22- Rawat, J.S., Kumar, M. 2015. Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1): 77-84.
23- Roostayee, Sh., Ahadnezhad Rooshti, M., Farrokhe Someae, M. 2015. Spatial evaluation of urban sprawl with an emphasize on landuse charges, using satellite imagery (Case study of Urmia). Geography and Planning, 18(50): 189-206.
_||_
4- He, Ch., Okada, N., Zhang, Q., Shi, P., Li, J. 2008. Modelling dynamic urban expansion processes incorporating a potential model with cellular automata. Landscape and Urban Planning, 86(1): 79-91.
11- Dadashpoor, H., Jahanzad, N. 2015. Simulation of future land use changes based on an ecological optimal pattern in Mashhad Metropolitan area. Geographical Urban Planning Research, 3(3): 343-359. (In Persian)
12- Maboodi, M.T., Hakimi, H. 2015. Analysis of land use changes and urban sprawl simulation in mid-sized cities (Case study: Khoy City). Geographical Urban Planning Research, 3(2): 211-226. (In Persian)
16- Jokar Arsanjani, J., Helbich, M., Kainz, W., Darvishi Boloorani, A. 2013. Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21: 265-275.
18- Poor Ahmad, A., Ziari, K.A., Mohammadi, R. Spatial distribution pattern of urban uses in oil-rich cities (Case study: Dogonbadan city). Geographical Research, 25: 21-50. (In Persian)
19- Bali, A., Monavari, S.M., Jafari, M., Abdolahi, Sh. 2012. Land uses change patterns in Anzali Wetland basin during 2000, 1989, 1975 and 2007 with emphasis on urban development and constructed lands. Journal of Environmental Science and Bioengineering, 53-54: 73-80. (In Persian)
20- Eerens, H., Haesen, D., Rembold, F., Urbano, F., Tote, C., Bydekerke, L. 2014. Image time series processing for agriculture monitoring. Environmental Modelling & Software, 53: 154-162.
21- Butt, A., Shabbir, R., Ahmad, S.S., Aziz, N. 2015. Land use change mapping and analysis using Remote Sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan. The Egyptian Journal of Remote Sensing and Space Science, 18(2): 251-259.
22- Rawat, J.S., Kumar, M. 2015. Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1): 77-84.
23- Roostayee, Sh., Ahadnezhad Rooshti, M., Farrokhe Someae, M. 2015. Spatial evaluation of urban sprawl with an emphasize on landuse charges, using satellite imagery (Case study of Urmia). Geography and Planning, 18(50): 189-206.