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Sustainability 2018, 10(9), 3116;

MCR-Modified CA–Markov Model for the Simulation of Urban Expansion

Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
Guangzhou Institute of Geography, Guangzhou 510070, China
Author to whom correspondence should be addressed.
Received: 6 July 2018 / Revised: 21 August 2018 / Accepted: 28 August 2018 / Published: 31 August 2018
(This article belongs to the Special Issue Data Analytics on Sustainable, Resilient and Just Communities)
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Ecosystem balance is an important factor that affects healthy and sustainable urban development. The traditional cellular automata (CA) model considers only a few ecological factors, however, the MCR model can account for ecological factors. In previous studies, few ecological factors were added to the CA model. Thus, the minimal cumulative resistance (MCR) model is combined with the CA and Markov models for the simulation of urban expansion. To verify the reliability of the method, the Wuhan metropolitan area was selected as a representative urban area, and its expansion in the past and future was simulated. Firstly, seven influential factors were selected from the perspective of location theory. The transformation rules of the comprehensive resistance surface followed by the modified CA–Markov model were constructed on the basis of the MCR model. The expansion of the Wuhan metropolitan area in 2013 was simulated on the basis of the 1996 and 2006 maps of land-use status, and the kappa coefficient was used as an index to evaluate the accuracy of the proposed method. Then, the expansion of the Wuhan metropolitan area in 2020 was simulated. Finally, the simulation results obtained with and without the MCR model were compared and analysed from the macro- and micro levels. Results show that the prediction accuracy of the two models differed for ecological regions, such as woodlands and water bodies. The similarities between the regions that were overestimated and underestimated by the MCR-modified CA–Markov model and non-MCR model may be attributed to solution of the land-use transfer matrix with the Markov model. The accuracy of the MCR-modified CA–Markov model for predicting forests, water and other ecological regions was higher than that of the Markov model. Therefore, the proposed MCR-modified CA–Markov model has potential applications in environmentally-conscious urban expansion. View Full-Text
Keywords: minimal cumulative resistance; Markov; cellular automata; urban expansion simulation minimal cumulative resistance; Markov; cellular automata; urban expansion simulation

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Li, X.; Wang, M.; Liu, X.; Chen, Z.; Wei, X.; Che, W. MCR-Modified CA–Markov Model for the Simulation of Urban Expansion. Sustainability 2018, 10, 3116.

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