A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata

This paper proposes a spatiotemporal model of land use change based on ant colony optimization (ACO), Markov chain and cellular automata (CA). These three methodologies have previously been used separately or in pairs to simulate land use change. In this paper, we apply them in combination, using ant colony optimization and cellular automata to manage the spatial distribution of land use, and applying Markov chain and cellular automata to manage the total amount of land use coverage. We first describe the principle and implementation of the model. Then a land use map of an experimental area (Changping, a district of Beijing) based on land use maps from 1988 and 1998 is simulated for 2008 using the model. By analyzing with real situation, accuracy of the simulation result manifests that the model is useful for land use change simulation. And compared with the other two models (CA–Markov model and ACO–CA model), the model is more appropriate in predicting both the quantity and spatial distribution of land use change in the study area. Therefore the model proposed by this paper is capable of simulating land use change.

[1]  Jia Tao,et al.  Discovery of transition rules for geographical cellular automata by using ant colony optimization , 2007 .

[2]  Yun Chen,et al.  Modeling and implementation of classification rule discovery by ant colony optimisation for spatial land-use suitability assessment , 2011, Comput. Environ. Urban Syst..

[3]  Luo Ping,et al.  Cellular Automata Based on Geographic Feature and Urban Land Use Evolvement , 2004 .

[4]  Long Ai-hua.  Spatio-temporal Simulation of Land Use Change Based on a Extended CA Model: A Case Study of Shenzhen City, China , 2011 .

[5]  Wu Zhifeng.  Analysis and Simulation of Land-Use Temporal and Spatial Pattern Based on CA-Markov Model , 2007 .

[6]  Jianyu Yang,et al.  Simulation of land use spatial pattern of towns and villages based on CA-Markov model , 2011, Math. Comput. Model..

[7]  Damian Clancy,et al.  Quantifying parameter uncertainty in a coral reef model using Metropolis-Coupled Markov Chain Monte Carlo , 2010 .

[8]  Lin Liu,et al.  A bottom‐up approach to discover transition rules of cellular automata using ant intelligence , 2008, Int. J. Geogr. Inf. Sci..

[9]  Yang Qing.  Integration of Multi-agent Systems with Cellular Automata for Simulating Urban Land Expansion , 2007 .

[10]  Chen Chongcheng,et al.  Land Use Change Simulation Model Based on MCDM and CA and Its Application , 2008 .

[11]  Min Ji,et al.  A case-based reasoning approach for land use change prediction , 2010, Expert Syst. Appl..

[12]  Jianguo Wu,et al.  Simulating spatiotemporal dynamics of urbanization with multi-agent systems—A case study of the Phoenix metropolitan region, USA , 2011 .

[13]  Xiaoping Liu,et al.  Coupling urban cellular automata with ant colony optimization for zoning protected natural areas under a changing landscape , 2011, Int. J. Geogr. Inf. Sci..

[14]  Michael R. Muller,et al.  A Markov model of land-use change dynamics in the Niagara Region, Ontario, Canada , 1994, Landscape Ecology.

[15]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[16]  Ali Onder Bozdogan,et al.  Improved assignment with ant colony optimization for multi-target tracking , 2011, Expert Syst. Appl..

[17]  Anthony Gar-On Yeh,et al.  Neural-network-based cellular automata for simulating multiple land use changes using GIS , 2002, Int. J. Geogr. Inf. Sci..

[18]  Shuying Zang,et al.  An aggregated multivariate regression land-use model and its application to land-use change processes in the Daqing region (northeast China) , 2006 .

[19]  Niklaus E. Zimmermann,et al.  Assessing land-use statistics to model land cover change in a mountainous landscape in the European Alps , 2008 .

[20]  J. W. Bruce,et al.  The causes of land-use and land-cover change: moving beyond the myths , 2001 .

[21]  F. Wu,et al.  Simulation of Land Development through the Integration of Cellular Automata and Multicriteria Evaluation , 1998 .

[22]  Weijun Gao,et al.  Land use change of Kitakyushu based on landscape ecology and Markov model , 2008 .

[23]  Alexander Zamyatin,et al.  MARKOV PROCESSES IN MODELING LAND USE AND LAND COVER CHANGES IN SINTRA-CASCAIS, PORTUGAL , 2009 .

[24]  Betul Yagmahan,et al.  Mixed-model assembly line balancing using a multi-objective ant colony optimization approach , 2011, Expert Syst. Appl..

[25]  Reiner Doluschitz,et al.  The impact of variation in scale on the behavior of a cellular automata used for land use change modeling , 2010, Comput. Environ. Urban Syst..

[26]  Jean-Christophe Castella,et al.  Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam , 2007 .

[27]  Roger White,et al.  Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns , 1993 .

[28]  Bo Huang,et al.  Land-Use-Change Modeling Using Unbalanced Support-Vector Machines , 2009 .

[29]  Paloma Ruiz-Benito,et al.  Land use change in a Mediterranean metropolitan region and its periphery: Assessment of conservation policies through CORINE land cover data and Markov models , 2010 .

[30]  Patrick R. McMullen,et al.  An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives , 2001, Artif. Intell. Eng..

[31]  Jinyan Zhan,et al.  Integration of Multiple Data Sources to Simulate the Dynamics of Land Systems , 2008, Sensors.

[32]  Harald Bugmann,et al.  Predicting long-term development of abandoned subalpine conifer forests in the Swiss National Park , 2009 .

[33]  Lin Wang,et al.  Simulation of precise scale land use change based on the Markov-cellular automata model , 2010, 2010 18th International Conference on Geoinformatics.

[34]  Jing Deng,et al.  Study on LUCC Based on Vector Date Source Using the CA_Markov Model: A Case Study of Changping District, Beijing, China , 2010, 2010 International Conference on Multimedia Technology.

[35]  PETER H. VERBURG,et al.  Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model , 2002, Environmental management.