A Review of Simulation Urban Growth Model
Keywords:Urban Growth, Geographic Information System, Simulation, Modeling.
Urban development has become a problem in many cities, especially in developing countries. The availability of areas for development is needed to deal with rapid population growth and urbanization. The purpose of this study was to identify urban growth models. Due to urban growth planning, the city will be more manageable and organized. From the conclusions of urban modeling identification can provide an idea of what model is appropriate for use in urban growth studies. The results of this urban growth model identification could be a reference in urban growth modeling in better urban planning.
 M. K. Jat, M. Choudhary, and A. Saxena, â€œApplication of geo-spatial techniques and cellular automata for modelling urban growth of a heterogeneous urban fringe,â€ Egypt. J. Remote Sens. Sp. Sci., 20(2), 223â€“241, 2017.
 M. M. Aburas, Y. M. Ho, M. F. Ramli, and Z. H. Ashâ€™aari, â€œImproving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio,â€ Int. J. Appl. Earth Obs. Geoinf., 59, 65â€“78, 2017.
 K. S. Kumar, K. P. Kumari, and P. U. Bhaskar, â€œApplication of Markov Chain & Cellular Automata based model for prediction of Urban transitions,â€ Proceedings of the Int. Conf. Electr. Electron. Optim. Tech., pp. 4007â€“4012, 2016.
 M. Ai-Ageili, M. Mouhoub, and J. Piwowar, â€œIntegrating remote sensing, GIS and dynamic models: Cellular automata approach for the simulation of urban growth for the city of Montreal,â€ Proceedings of the Can. Conf. Electr. Comput. Eng., pp. 1â€“6, 2013.
 K. Abutaleb and F. Ahmed, â€œModeling of urban change using remote sensing data and cellular automata technique,â€ Arab. J. Geosci., 9(15), 1â€“10, 2016.
 M. Jafari, H. Majedi, S. Monavari, A. Alesheikh, and M. Kheirkhah Zarkesh, â€œDynamic simulation of urban expansion based on cellular automata and logistic regression model: Case study of the Hyrcanian Region of Iran,â€ Sustainability, 8(8), 1-18, 2016.
 A. Siddiqui, A. Siddiqui, S. Maithani, A. K. Jha, P. Kumar, and S. K. Srivastav, â€œUrban growth dynamics of an Indian metropolitan using CA Markov and Logistic Regression,â€ Egypt. J. Remote Sens. Sp. Sci., 2017, 1-8, 2017.
 T. Munshi, M. Zuidgeest, M. Brussel, and M. van Maarseveen, â€œLogistic regression and cellular automata-based modelling of retail, commercial and residential development in the city of Ahmedabad, India,â€ Cities, 39, 68â€“86, 2014.
 S. Saeedi, â€œIntegrating macro and micro scale approaches in the agent-based modeling of residential dynamics,â€ Int. J. Appl. Earth Obs. Geoinf., 68, 214â€“229, 2018.
 S. T. Lee, C. W. Wu, and T. C. Lei, â€œCA-GIS model for dynamic simulation of commercial activity development by the combination of ANN and Bayesian probability,â€ Procedia Comput. Sci., 18, 651â€“660, 2013.
 H. Dadashpoor and M. Nateghi, â€œSimulating spatial pattern of urban growth using GIS-based SLEUTH model: A case study of eastern corridor of Tehran metropolitan region, Iran,â€ Environ. Dev. Sustain., 19(2), 527â€“547, 2017.
 D. Triantakonstantis and G. Mountrakis, â€œUrban growth prediction: A review of computational models and human perceptions,â€ 2012, 555â€“587, 2012.
 B. Bhatta, Analysis of Urban Growth and Sprawl from Remote Sensing Data. Springer, 2010.
 X. Liu, L. Ma, X. Li, B. Ai, S. Li, and Z. He, â€œSimulating urban growth by integrating landscape expansion index (LEI) and cellular automata,â€ Int. J. Geogr. Inf. Sci., 28(1), 148â€“163, 2014.
 A. El Garouani, D. J. Mulla, S. El Garouani, and J. Knight, â€œAnalysis of urban growth and sprawl from remote sensing data: Case of Fez, Morocco,â€ Int. J. Sustain. Built Environ., 6(1), 160â€“169, 2017.
 M. Kindu, T. Schneider, M. DÃ¶llerer, D. Teketay, and T. Knoke, â€œScenario modelling of land use/land cover changes in Munessa-Shashemene landscape of the Ethiopian highlands,â€ Sci. Total Environ., 622â€“623, 534â€“546, 2018.
 H. Shafizadeh-Moghadam, A. Asghari, M. Taleai, M. Helbich, and A. Tayyebi, â€œSensitivity analysis and accuracy assessment of the land transformation model using cellular automata,â€ GIScience Remote Sens., 54(5), 639â€“656, 2017.
 K. R. Dahal and T. E. Chow, â€œAn agent-integrated irregular automata model of urban land-use dynamics,â€ Int. J. Geogr. Inf. Sci., 28(11), 2281â€“2303, 2014.
 A. A. A. Al-sharif and B. Pradhan, â€œMonitoring and predicting land use change in Tripoli Metropolitan City using an integrated Markov chain and cellular automata models in GIS,â€ Arab. J. Geosci., 7(10), 4291â€“4301, 2014.
 L. Chen and W. Nuo, â€œDynamic simulation of land use changes in Port City: A case study of Dalian, China,â€ Procedia - Soc. Behav. Sci., 96, 981â€“992, 2013.
 Y. Liu, Y. Hu, S. Long, L. Liu, and X. Liu, â€œAnalysis of the effectiveness of urban land-use-change models based on the measurement of spatio-temporal, dynamic urban growth: A cellular automata case study,â€ Sustain., 9(5), 1â€“15, 2017.
 I. M. I. M. Brunner, â€œPrediction of Urban Growth Using the Bucket Model,â€ Procedia - Soc. Behav. Sci., 227, 3â€“10, 2016.
 S. Åžalap-AyÃ§a, P. Jankowski, K. C. Clarke, P. C. Kyriakidis, and A. Nara, â€œA meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: An application for a cellular automata-based Urban growth and land-use change model,â€ Int. J. Geogr. Inf. Sci., 32(4), 637â€“662, 2018.
 F. Yao, C. Hao, and J. Zhang, â€œSimulating urban growth processes by integrating cellular automata model and artificial optimization in Binhai New Area of Tianjin, China,â€ Geocarto Int., 31(6), 612â€“627, 2016.
 X. Li, X. Liu, and L. Yu, â€œA systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules,â€ Int. J. Geogr. Inf. Sci., 28(7), 1317â€“1335, 2014.
 Y. Zhou, Ye, F. Zhang, Z. Du, X. Ye, and R. Liu, "Integrating cellular automata with the deep belief network for simulating urban growth," Sustainability, 9(10), 1-19, 2017.
 N. Pinto, A. P. Antunes, and J. Roca, â€œApplicability and calibration of an irregular cellular automata model for land use change,â€ Comput. Environ. Urban Syst., 65, 93â€“102, 2017.
 M. Jafari, H. Majedi, S. M. Monavari, A. A. Alesheikh, and M. K. Zarkesh, â€œDynamic simulation of urban expansion through a CA-markov model case study: Hyrcanian region, Gilan, Iran,â€ Eur. J. Remote Sens., 49, 513â€“529, 2016.
 C. A. Ku, â€œIncorporating spatial regression model into cellular automata for simulating land use change,â€ Appl. Geogr., 69, 1â€“9, 2016.
 X. Li, P. Gong, L. Yu, and T. Hu, â€œA segment derived patch-based logistic cellular automata for urban growth modeling with heuristic rules,â€ Comput. Environ. Urban Syst., 65, 140â€“149, 2017.
 X. Zhang, X. Lin, and S. Zhu, â€œModeling urban growth by cellular automata: A case study of Xiamen City, China,â€ Proceedings of the IEEE 10th International Conference on Computer Science and Education, pp. 645â€“650, 2015.
 Y. Sakieh, B. J. Amiri, A. Danekar, J. Feghhi, and S. Dezhkam, â€œSimulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran,â€ J. Hous. Built Environ., 30(4), 591â€“611, 2015.
 N. Bihamta, A. Soffianian, S. Fakheran, and M. Gholamalifard, â€œUsing the SLEUTH urban growth model to simulate future urban expansion of the Isfahan Metropolitan Area, Iran,â€ J. Indian Soc. Remote Sens., 43(2), 407â€“414, 2015.
 K. C. Clarke, â€œA decade of cellular urban modeling with SLEUTH: Unresolved issues and problems,â€ in R. K. Brail, (Ed.), Planning Support Systems for Cities and Regions. Massachusetts: Lincoln Institute of Land Policy, pp. 47â€“60, 2008.
 H. Yin, F. Kong, Y. Hu, P. James, F. Xu, and L. Yu, â€œAssessing growth scenarios for their landscape ecological security impact using the SLEUTH urban growth model,â€ J. Urban Plan. Dev., 142(2), 1-13, 2016.
 M. Al-shalabi, L. Billa, B. Pradhan, S. Mansor, and A. A. A. Al-Sharif, â€œModelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: The case of Sanaâ€™a metropolitan city, Yemen,â€ Environ. Earth Sci., 70(1), 425â€“437, 2013.
 Y. Liang and L. Liu, â€œModeling urban growth in the middle basin of the Heihe River, northwest China,â€ Landsc. Ecol., 29(10), 1725â€“1739, 2014.
 G. Grekousis, Y. N. Photis, and G. Grekousis, â€œAnalyzing High-Risk Emergency Areas with GIS and Neural Networks: The Case Networks: The case of Athens , Greece,â€ The Professional Geographer, 66(1), 37â€“41, 2014.
 G. Grekousis, P. Manetos, and Y. N. Photis, â€œModeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area,â€ Cities, 30(1), 193â€“203, 2013.
 A. D. Aarthi and L. Gnanappazham, â€œUrban growth prediction using neural network coupled agents-based Cellular Automata model for Sriperumbudur Taluk, Tamil Nadu, India,â€ Egypt. J. Remote Sens. Sp. Sci., 2018, 1-10, 2018.
 S. I. Musa, M. Hashim, and M. N. Reba, â€œA review of geospatial-based urban growth models and modelling initiatives,â€ Geocarto International, 32(8), 813-833, 2017.
  E. PÃ©rez-Molina, R. Sliuzas, J. Flacke, and V. Jetten, â€œDeveloping a cellular automata model of urban growth to inform spatial policy for flood mitigation: A case study in Kampala, Uganda,â€ Comput. Environ. Urban Syst., 65, 53â€“65, 2017.
 M. Azari, A. Tayyebi, M. Helbich, and M. A. Reveshty, â€œIntegrating cellular automata, artificial neural network, and fuzzy set theory to simulate threatened orchards: Application to Maragheh, Iran,â€ GIScience Remote Sens., 53(2), 183â€“205, 2016.
 X. Fu, X. Wang, and Y. J. Yang, â€œDeriving suitability factors for CA-Markov land use simulation model based on local historical data,â€ J. Environ. Manage., 206, 10â€“19, 2018.
 M. Aljoufiea, M. Brussel, M. Zuidgeest, and M. van Maarseveen, â€œUrban growth and transport infrastructure interaction in Jeddah between 1980 and 2007,â€ Int. J. Appl. Earth Obs. Geoinf., 21(1), 493â€“505, 2012.
 H. Shafizadeh-Moghadam, A. Tayyebi, and M. Helbich, â€œTransition index maps for urban growth simulation: Application of artificial neural networks, weight of evidence and fuzzy multi-criteria evaluation,â€ Environ. Monit. Assess., 189(6), 1-14, 2017.
 K. Marko, F. Zulkarnain, and E. Kusratmoko, â€œCoupling of Markov chains and cellular automata spatial models to predict land cover changes (Case study: Upper Ci Leungsi catchment area),â€ IOP Conf. Ser. Earth Environ. Sci., 47(1), 2016.
View Full Article:
How to Cite
LicenseAuthors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under aÂ Creative Commons Attribution Licensethat allows others to share the work with an acknowledgement of the work''s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal''s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (SeeÂ The Effect of Open Access).