Document Type : CASE STUDY


Department of Watershed Management, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran


Mashhad City, according to the latest official statistics of the country is the second populated city after Tehran and is the biggest metropolis in the east of Iran. Considering the rapid growth of the population over the last three decades, the city’s development area has been extended, significantly. This significant expansion has impacted natural lands on suburb and even some parts e.g. rangelands and agricultural area have been transited to urban land uses. The study was aimed at analyzing and simulating land use changes in Mashhad, Iran. The work needs a model to simulate land use changes among multiple categories and combine spatial and temporal changes during the projection period. Thus, Cellular Automata-Markov model was chosen to meet this target. In this work, the projected time period corresponded to the final 20-year vision period of all-round development of Iran for the target point of  2025 based on a long-term plan. Multi criteria evaluation approach integrated along with analytic hierarchy process were employed for preparing suitability maps for the five land uses, i.e. urban continuous patches, urban discontinuous patches, rural patches, agricultural lands, and range lands. Having applied the matrices utilized in model calibration, the best kappa coefficient proved to be associated with the land use maps dated 1996 and 2002. The Kappa index of quantity and allocation agreement was determined to be 0.9189 and 0.9529, respectively, which established an almost perfect agreement between simulated and observed land uses according to the year 2015. Change detection results showed that with the physical expansion of urban continuous patches, range lands and agricultural lands mostly transited to urban discontinuous patches and eventually were promoted to urban continuous texture. These developments or gains in urbanized patches will lead to some loses in agricultural lands and rangelands of the suburb in 2025. In addition, the analysis of projected land use map indicated that over the upcoming years, the development of the city in northern front, especially in northwestern region will be more intense with a higher speed in comparison with the other regions.

Graphical Abstract

Analyzing and modeling urban sprawl and land use changes in a developing city using a CA-Markovian approach


  • Using CA-Markov for land use/ cover change modeling and analyzing model validation
  • LUCC modeling of the second largest city in Iran for the target point of 2025
  • Investigating the impact of urban sprawl on suburb rangelands and agricultural activities


Main Subjects

Alizadeh, M.; Ngah, I.; Shahabi, H.; Ali zade, E., (2013). Evaluating AHP and WLC methods in site selection of waste landfill (Case study: Amol, North of Iran). J. Basic Appl. Sci. Res., 3(5), 83-88 (6 pages).
Alkheder, S.; Shan, J., (2005, 31 July - 3 August). Cellular Automata urban growth simulation and evaluation-A case study of Indianapolis. In Proceedings of the 8th International Conference on GeoComputation. pp. 1-19, University of Michigan, USA.
Araya, Y.H.; Cabral, P., (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sens., 2(6), 1549-1563 (15 pages).
Arsanjani, J.J.; Kainz, W.; Mousivand, A.J., (2011). Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran. Int. J. Image Data Fusion, 2(4), 329-345 (17 pages).
Bhatta, B., (2012). Urban Growth Analysis and Remote Sensing: A Case Study of Kolkata, India 1980–2010. Springer Science & Business Media.
Bozbura, F.T.; Beskese, A.; Kahraman, C., (2007). Prioritization of human capital measurement indicators using Fuzzy AHP. Expert Syst. Appl., 32(4), 1100-1112 (13 pages).
Cai, T.; Li, Q.; Yu, M.; Lu, G.; Cheng, L.; Wei, X., (2012). Investigation into the impacts of land-use change on sediment yield characteristics in the upper Huaihe River basin, China. Phys. Chem. Earth, Parts A/B/C, 53, 1-9 (9 pages).
Carletta, J., (1996). Assessing agreement on classification tasks: the kappa statistic. Comput. Ling., 22(2), 249-254 (6 pages).
Chang, D.Y., (1996). Applications of the extent analysis method on fuzzy AHP. Europ. J. Oper. Res., 95(3), 649–655 (7 pages).
Cheng, S.K., (2000). Development of a fuzzy multi-criteria decision support system for municipal solid waste management,” Master Thesis, Applied Science in Advanced Manufacturing and Production Systems, University of Regina, Canada, 2000.
Cohen, B., (2006). Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability. Technol. society, 28(1), 63-80 (18 pages).
Cohen, J., (1960). A coefficient of agreement for nominal scale. Educ. Psychol. Meas., 20, 37-46 (10 pages).
Darvishi, Y.; Masoumi, D., (2013). Marginalization and its role in social pathos (Case study: Ardebil city). Int. Res. J. Appl. Basic Sci., 7(5), 284-287 (4 pages).
Donnay, J.P.; Barnsley, M.; Longley, P.A., (2001). Remote sensing and urban analysis. Taylor & Francis, London.
Eastman, J.R., (2006). IDRISI Andes guide to GIS and image processing. Clark University, Worcester, 87-131 (45 pages).
Herold, M.; Roberts, D.A.; Gardner, M.E.; Dennison, P.E., (2004). Spectrometry for urban area remote sensing—Development and analysis of a spectral library from 350 to 2400 nm. Remote Sens. Environ., 91(3), 304-319 (16 pages).
Iran’s Statistic Center (2015). Popular census report on population and housing. Accessed through:
Jenerette, G.D.; Wu, J., (2001). Analysis and simulation of land-use change in the central Arizona–Phoenix region, USA. Landsc. Ecol., 16(7), 611-626 (16 pages).
Jensen, J.R.; Lulla, K., (1987). Introductory digital image processing: a remote sensing perspective. Taylor & Francis.
Kundel, H.L.; Polansky, M., (2003). Measurement of Observer Agreement 1. Radiology, 228(2), 303-308 (6 pages).
Li, J.; Deng, J.; Wang, K.; Li, J.; Huang, T.; Lin, Y.; Yu, H., (2014). Spatiotemporal patterns of urbanization in a developed region of eastern coastal China. Sustainability, 6(7), 4042-4058 (17 pages).
Li, J.; Rahman, M.H.; Thring, R.W., (2010). A fuzzy multi-criteria decision analysis approach for the management of petroleum-contaminated sites. Int. J. Environ. Pollut., 42(1-3), 220-239 (20 pages).
Markov, A., (1971). Extension of the limit theorems of probability theory to a sum of variables connected in a chain. The Notes of the Imperial Academy of Sciences of St. Petersburg, VIII Series, Physio-Mathematical College XXII.
Memarian, H.; Balasundram, S.K.; Abbaspour, K.C.; Talib, J.B.; Sung, C.T.B.; Sood, A.M., (2015). Integration of analytic hierarchy process and weighted goal programming for land use optimization at the watershed scale. Turkish J. Eng. Env. Sci., 38(2), 139-158 (20 pages).
Memarian, H.; Balasundram, S.K.; Abbaspour, K.C.; Talib, J.B.; Boon Sung, C.T.; Sood, A.M., (2014). SWAT-based hydrological modelling of tropical land-use scenarios. Hyd. Sci. J., 59(10), 1808-1829 (22 pages).
Memarian, H.; Balasundram, S.K.; Talib, J.B.; Teh Boon Sung, C.; Mohd Sood, A.; Abbaspour, K.C., (2013). KINEROS2 application for land use/cover change impact analysis at the Hulu Langat Basin, Malaysia. Water Environ. J., 27(4), 549-560 (12 pages).
Memarian, H.; Balasundram, S.K.; Talib, J.B.; Sung, C.T.B.; Sood, A.M.; Abbaspour, K., (2012). Validation of CA-Markov for simulation of land use and cover change in the Langat Basin, Malaysia. J. Geogr. Inf. Syst., 4(6), 542-554 (13 pages).
Mendoza, G.A.; Martins, H., (2006). Multi-criteria decision analysis in natural resource management: A critical review of methods and new modeling paradigms. Forest Ecol. Manag., 230(1-3), 1 – 22 (23 pages).
Nouri, J.; Gharagozlou, A.; Arjmandi, R.; Faryadi, S.; Adl, M., (2014). Predicting urban land use changes using a CA–Markov model. Arab. J. Sci. Eng., 39(7), 5565-5573 (9 pages).
Oguztimur, S., (2011). Why fuzzy analytic hierarchy process approach for transport problems?. Available from: [Accessed 17 June 2016].
Saaty, T.L., (2000). The fundamentals of decision making and priority theory with the analytic hierarchy process. University of Pittsburgh, RWS Publications, Pittsburgh, PA 15260, USA.
Saaty, T.L., (1990). How to make a decision: the analytic hierarchy process. Eur. J. Oper. Res., 48(1), 9-26 (18 pages).
Saaty, T.L., (1980). The Analytic Hierarchy Process. McGraw- Hill, New York.
Samat, N., (2009). Integrating GIS and CA-MARKOV model in evaluating urban spatial growth. Malaysian J. Environ. Manag., 10(1), 83-99 (17 pages).
Samat, N.; Hasni, R.; Elhadary, Y.A.E., (2011). Modelling land use changes at the peri-urban areas using geographic information systems and cellular automata model. J. Sust. Dev., 4(6), 72.
Wang, L.; Hu, H.; Zheng, X.; Deng, J.; Ning, G., (2010, 29 October – 31 October). Study on LUCC Based on Vector Date Source Using the CA_Markov Model: A Case Study of Changping District, Beijing, China. In Multimedia Technology (ICMT), 2010 International Conference. pp. 1-4. IEEE, China.
Wang, Y.; Li, S., (2011). Simulating multiple class urban land-use/cover changes by RBFN-based CA model. Comput. Geosci., 37(2), 111-121 (11 pages).
Westhoek, H.J.; Van den Berg, M.; Bakkes, J.A., (2006). Scenario development to explore the future of Europe's rural areas. Agri. Ecosyst. Environ., 114(1), 7-20 (14 pages).
Zadeh, L.A., (2008). Is there a need for fuzzy logic?. Inform. Sciences, 178(13), 2751-2779 (29 pages)

Letters to Editor

GJESM Journal welcomes letters to the editor for the post-publication discussions and corrections which allows debate post publication on its site, through the Letters to Editor. Letters pertaining to manuscript published in GJESM should be sent to the editorial office of GJESM within three months of either online publication or before printed publication, except for critiques of original research. Following points are to be considering before sending the letters (comments) to the editor.

[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.
[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.
[3] Letters can be no more than 300 words in length.
[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.
[5] Anonymous letters will not be considered.
[6] Letter writers must include their city and state of residence or work.
[7] Letters will be edited for clarity and length.