Department of Environmental Planning and Management, Graduate Faculty of Environment, University of Tehran, Tehran, Iran
Analyzing the process of land use and cover changes during long periods of time and predicting the future changes is highly important and useful for the land use managers. In this study, the land use maps in the Ardabil plain in north-west part of Iran for four periods (1989, 1998, 2009 and 2013) are extracted and analyzed through remote sensing technique, using the land-sat satellite images. Then, the future land use changes are simulated for 2030 using integrated CA-Markov model according to the scenario of continuing current management process. The results show that in the period between 1989 and 2009, i.e. since two-thirds of the plain was declared restricted till all of it was declared thus, the study area has experienced a total of about 58645.08 ha changes. After the whole plain was restricted (since 2009 till 2014), the changes have been estimated to be 22466.88 ha. The prediction also indicates that the changes will equal 8908.83 ha by 2030. Agricultural lands and human-built environment constitute the majority of changes and are increasing continuously. The obtained Kappa values for the model accuracy assessment (higher than 0.8) indicated the model's capability to predict future Land use/cover changes in the study area. Thus, analyzing Land use and cover changes trends from past to near future using CA-Markov model can play a significant role in land use policy making, planning, and managing of the restricted plains especially in the proposed study area.
Analyzing LUCCs trends from past to near future using CA-Markov model plays a significant role in land use policy making, planning, and managing of the restricted plains
Human-built environment and agricultural land use constitute the main dynamics of changes
CA-Markov model capability to predict future LUCCs in the study area
Aalipour Erdi, M., (2014). Land subsidence risk assessment causing due to decline ground water: Case study Ardabil plain. Master of Science Thesis, University of Tehran. Iran.
Abanpajoh, Enginieers Co., (2015). Ardabil water supply projects. In: COMPANY, E. (ed.). Ministry of Energy, Iran.
Adhikari, S.; Southworth, J., (2012). Simulating forest cover changes of Bannerghatta National Park based on a CA-Markov model: A remote sensing approach. Remote Sens., 4(10): 3215-3243 (29 pages).
Agarwal, C.; Green, G. M.; Grove, J. M.; Evans, T. P; Schweik, C. M., (2002). A review and assessment of land-use change models: dynamics of space, time, and human choice, 1-61 (61 pages).
Al-sharif, A.A.; Pradhan, B., (2014). Monitoring and predicting land use change in Tripoli Metropolitan City using an integrated Markov chain and cellular automata models in GIS. Arab J Geosci, 7(10): 4291-4301 (11 pages).
Amini Parsa, V., (2014). Modeling Plausible Impacts of Land Use Changes of the Surrounding Buffer Zone on the Management of the Arasbaran Biosphere Reserve. MSc thesis, University of Tehran. Iran.
Arsanjani, J.J.; Helbich, M.; Kainz, W.; Boloorani, A.D., (2013). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. Int. J. Appl. Earth. Obs., 21: 265-275 (11 pages).
Batisani, N.; Yarnal, B., (2009). Urban expansion in Centre County, Pennsylvania: Spatial dynamics and landscape transformations. Appl. Geogr., 29(2): 235-249 (15 pages).
Behera, M.D.; Borate, S.N.; Panda, S.N.; Behera, P.R.; Roy, P.S., (2012). Modelling and analyzing the watershed dynamics using Cellular Automata (CA)–Markov model–A geo-information based approach. J. Earth Syst. Sci., 121(4): 1011-1024 (14 pages).
Brown, D.G.; Pijanowski, B.C.; Duh, J., (2000) . Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA. J. Environ. Manage., 59(4): 247-263 (17 pages).
Daneshvar Vousoughi, F.; Dinpashoh, Y., (2013). Trends of Groundwater Quality of Ardabil Plain Using the Spearman Method. Jes, 38(64): 17-28 (12 pages).
Dubovyk, O.; Sliuzas, R.; Flacke, J., (2011). Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey. Isprs. J. Photogramm., 66(2): 235-246 (12 pages).
Farsaei, M., (2012). Urban phenomena simulation based on cellular automata. MSc Thesis, University of Tehran. Iran.
Foody, G. M., (2002). Status of land cover classification accuracy assessment. Remote Sens Environ, 80(1): 185-201 (17 pages).
Ghodsniroo, (2009). Semi-detailed studies of groundwater in Ardabil province. In: COMPANY, E. (Ed.). Iran: Ministry of Energy.
Gong, W.; Yuan, L.; Fan, W.; Stott, P., (2015). Analysis and simulation of land use spatial pattern in Harbin prefecture based on trajectories and cellular automata, Markov modelling. Int. J. Appl. Earth Obs., 34: 207-216 (10 pages).
Halmy, M.W.; Gessler, P.E.; Hicke, J.A.; Salem, B.B., (2015). Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA. Applied Geography. Appl. Geogr, 63(2): 101-112 (13 pages).
Houet, T.; Hubert-Moy, L., (2006). Modeling and projecting land-use and land-cover changes with Cellular Automaton in considering landscape trajectories. EARSeL e-Proceedings, 5(1): 63-76 (14 pages).
Jiang, W.; Chen, Z.; Lei, X.; Jia, K.; Wu, Y., (2015). Simulating urban land use change by incorporating an autologistic regression model into a CLUE-S model. J. Geogr. Sci, 25(7): 836-850 (15 pages).
Kord, M.; Moghaddam, A.A., (2014). Spatial analysis of Ardabil plain aquifer potable groundwater using fuzzy logic. King Saud University-S, 26(2): 129-140 (12 pages).
Luo, G.; Amuti, T.; Zhu, L.; Mambetov, B.T.; Maisupova, B.; Zhang, C., (2015). Dynamics of landscape patterns in an inland river delta of Central Asia based on a cellular automata-Markov model. Reg Environ Change, 15(2): 277-289 (13 pages).
Maali, Ahari, N., (2011). Investigation the role of groundwater withdrawal on future possible subsidence in Ardabil plain by using GIS. M. A Thesis, Tarbiat Moallem University. Iran.
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).
Milà, I.; Canals, L.; De Baan, L., (2015). Land Use. In: HAUSCHILD, M. Z.; HUIJBREGTS, M.A.J. (Eds.) Life cycle impact assessment. The Netherlands.
Muller, M.R.; Middleton, J., (1994). A Markov model of land-use change dynamics in the Niagara Region, Ontario, Canada. Landscape Ecol., 9(2): 151-157 (7 pages).
Nejadi, A.; Jafari, H.; Makhdoum, M.; Mahmoudi, M., (2012). Modeling Plausible Impacts of land use change on wildlife habitats, Application and validation: Lisar protected area, Iran, Int. J. Environ. Res, 6(4): 883-892 (10 pages).
Omar, N.Q.; Ahamad, M.S.S.; Hussin, W.M.A.W.; Samat, N., (2014). Modelling Land-use and Land-cover Changes Using Markov-CA, and Multiple Decision Making in Kirkuk City. IJSRES, 2(1): 29-42 (14 pages).
Parker, D.C.; Manson, S.M.; Janssen, M.A.; Hoffmann, M.J.; Deadman, P., (2003). Multi-agent systems for the simulation of land-use and land-cover change: A review. Ann. Assoc. Am. Geogr., 93(2): 314-337 (24 pages).
Poelmans, L.; Van Rompaey, A., (2010). Complexity and performance of urban expansion models., Comput. Environ. Urban, 34(1): 17-27 (11 pages).
Pontius, R. G., (2000). Quantification error versus location error in comparison of categorical maps. Photogramm. Eng. Rem. S., 66(8): 1011-1016 (6 pages).
Pontius, R.G.; Schneider, L.C., (2001). Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agric. Ecosyst. Environ., 85(1): 239-248 (10 pages).
Sang, L.; Zhang, C.; Yang, J.; Zhu, D.; Yun, W., (2011). Simulation of land use spatial pattern of towns and villages based on CA-Markov model. Math. Comput. Model., 54(3): 938-943 (6 pages).
Singh, A. K., (2003). Modelling land use land cover changes using cellular automata in a geo-spatial environment. Master of Science Thesis, International Institute for Geo-Information Science and Earth Observation. Enscheda. The Netherlands.
Subedi, P.; Subedi, K.; Thapa, B., (2013). Application of a Hybrid Cellular Automaton–Markov (CA-Markov) Model in land use change prediction: A case study of Saddle Creek Drainage Basin, Florida. Appl. Ecol. Environ. S, 1(6): 126-132 (7 pages).
Torrens, P.M.; O'Sullivan, D., (2001). Cellular automata and urban simulation: where do we go from here? Environment and Planning. B: Plan. Des., 28(2): 163-168 (6 pages).
van Vliet, J.; White, R.; Dragicevic, S., (2009). Modeling urban growth using a variable grid cellular automaton. Comput. Environ. Urban, 33(1): 35-43 (9 pages).
Veldkamp, A.; Verburg, P.H., (2004). Modelling land use change and environmental impact. J. Environ. Manage., 72(1): 1-3(3 pages).
Viera, A.J.; Garrett, J.M., (2005). Understanding interobserver agreement: the kappa statistic. Fam. Med., 37(5): 360-363 (4 pages).
White, R.; Engelen, G., (2000). High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Comput. Environ. Urban, 24(5): 383-400 (18 pages).
Zhang, H.; Jin, X.; Wang, L.; Zhou, Y.; Shu, B., (2015). Multi-agent based modeling of spatiotemporal dynamical urban growth in developing countries: simulating future scenarios of Lianyungang city, China. Stoch. Environ. Res. Risk A, 29(1): 63-78 (16 pages).
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