RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2017, Vol. 26 >> Issue (02): 190-197.doi: 10.11870/cjlyzyyhj201702004

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URBAN EXPANSION SIMULATION USING MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM AND CELLULAR AUTOMATA: A CASE STUDY OF NANJING CITY

LI Qin1,2, SHEN Ming1,2, GAO Yong-nian1, ZHANG Zhi-fei3   

  1. 1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China;
    2. University of the Chinese Academy of Sciences, Beijing 100049, China;
    3. Jiangsu Institute of Land Surveying and Planning, Nanjing 210024, China
  • Received:2016-05-23 Revised:2016-07-19 Online:2017-02-20
  • Supported by:
    Land Carrying Capacity Survey and Evaluation Project of the Ministry of Land and Resources in Key Regions (DCPJ131208-01);Land, Resources, Science and Technology Projects of Jiangsu Province (201204)

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Abstract: For scientific use of multi-agent algorithm to model dynamic urban growth, Subsection Particle Swarm Optimization (SPSO), an improved algorithm has been proposed in this paper. The improvement is based on the general rule in geography and sociology. Cellular Automata is also combined to simulate complex spatial-temporal processes. An new Geographic Cellular Automata (SPSO-CA) is constructed to achieve the dynamic simulation of urban growth. Deriving transition rules is key to the Geographic Cellular Automata. We therefore discover first the transition rules for SPSO-CA based on 1995-2000 land use data, traffic network data and terrain data. And then, dynamic simulation of urban expansion process of Nanjing City from 1995 to 2008 is made according to this rule. Lastly, in order to test the effectiveness of the improved algorithm, we compared SPSO-CA, PSO-CA and NULL model, the following results were obtained. The overall accuracy of SPSO-CA is 86.3%, with Kappa coefficient of 0.792, Moran's I of 0.078; the overall accuracy of PSO-CA is 83.6%, with Kappa coefficient of 0.755, actual Moran's I of 0.054; the overall accuracy of NULL model is 81.9%, with Kappa coefficient of 0.741, with actual Moran's I of 0.072. These results demonstrate that SPSO-CA is better than PSO-CA and NULL model and the improvement of Subsection Particle Swarm Optimization is available.

Key words: particle swarm optimization, cellular automata, land use, urban expansion, GIS, Nanjing

CLC Number: 

  • P209
[1] 邵晓梅, 刘庆, 张衍毓. 土地集约利用的研究进展及展望[J]. 地理科学进展, 2006, 25(2):85-95.[SHAO X M, LIU Q, ZHANG Y Y. Advances and expectations of intensive land use researches[J]. Progress in Geography, 2006, 25(2):85-95.]
[2] 谈明洪, 李秀彬, 吕昌河. 我国城市用地扩张的驱动力分析[J]. 经济地理, 2003, 23(5):635-639.[TAN M H, LI X B, LV C H. An analysis of driving forces of urban land expansion in China[J]. Economic Geography, 2003, 23(5):635-639.]
[3] BATTY M, XIE Y. From cells to cities[J]. Environment and Planning B:Planning and Design, 1994, 21(7):S31-S48, doi:10.1068/b21s031.[DOI:10.1068/b21s031]
[4] 韩玲玲, 何政伟, 唐菊兴, 等. 基于CA的城市增长与土地增值动态模拟方法探讨[J]. 地理与地理信息科学, 2003, 19(2):32-35.[HAN L L, HE Z W, TANG J X, et al. A study on dynamic simulation of urban growth and land value increment based on CA model[J]. Geography and Geo-Information Science, 2003, 19(2):32-35.]
[5] HE Y Q, AI B, YAO Y, et al. Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images[J]. International Journal of Applied Earth Observation and Geoinformation, 2015, 38:164-174.
[6] WANG H J, HE S W, LIU X J, et al. Simulating urban expansion using a cloud-based cellular automata model:a case study of Jiangxia, Wuhan, China[J]. Landscape and Urban Planning, 2013, 110:99-112.
[7] NOURI J, GHARAGOZLOU A, ARJMANDI R, et al. Predicting urban land use changes using a CA-Markov model[J]. Arabian Journal for Science and Engineering, 2014, 39(7):5565-5573.
[8] SANG L L, ZHANG C, YANG J Y, et al. Simulation of land use spatial pattern of towns and villages based on CA-Markov model[J]. Mathematical and Computer Modelling, 2011, 54(3/4):938-943.
[9] FENG Y J, LIU Y, TONG X H, et al. Modeling dynamic urban growth using cellular automata and particle swarm optimization rules[J]. Landscape and Urban Planning, 2011, 102(3):188-196.
[10] 刘小平, 黎夏, 叶嘉安, 等. 利用蚁群智能挖掘地理元胞自动机的转换规则[J]. 中国科学D辑:地球科学, 2007, 37(6):824-834.[LIU X P, LI X, YEH A G O, et al. Discovery of transition rules for geographical cellular automata by using ant colony optimization[J]. Science in China Series D:Earth Sciences, 2007, 50(10):1578-1588.]
[11] MA S F, HE J H, LIU F, et al. Land-use spatial optimization based on PSO algorithm[J]. Geo-Spatial Information Science, 2011, 14(1):54-61.
[12] 李爱国, 覃征, 鲍复民, 等. 粒子群优化算法[J]. 计算机工程与应用, 2002, 38(21):1-3, 17.[LI A G, QIN Z, BAO F M, et al. Particle swarm optimization algorithms[J]. Computer Engineering and Applications, 2002, 38(21):1-3, 17.]
[13] 周驰, 高海兵, 高亮, 等. 粒子群优化算法[J]. 计算机应用研究, 2003, 20(12):7-11.[ZHOU C, GAO H B, GAO L, et al. Particle swarm optimization (PSO) algorithm[J]. Application Research of Computers, 2003, 20(12):7-11.]
[14] 胥小波, 郑康锋, 李丹, 等. 新的混沌粒子群优化算法[J]. 通信学报, 2012, 33(1):24-30, 37.[XU X B, ZHENG K F, LI D, et al. New chaos-particle swarm optimization algorithm[J]. Journal on Communications, 2012, 33(1):24-30, 37.]
[15] NESHAT M, SEPIDNAM G, SARGOLZAEI M. Swallow swarm optimization algorithm:a new method to optimization[J]. Neural Computing and Applications, 2013, 23(2):429-454.
[16] 阳建逸. 基于蜂群智能的地理元胞自动机转换规则挖掘方法研究[D]. 南京:南京师范大学硕士学位论文, 2014.[YANG J Y. Research on discovering transition rules of geographic cellular automata based on bee colony optimization[D]. Nanjing:Master Dissertation of Nanjing Normal University, 2014.]
[17] 黎夏, 叶嘉安. 知识发现及地理元胞自动机[J]. 中国科学D辑:地球科学, 2004, 34(9):865-872.[LI X, YEH A G O. Knowledge discovery for geographical cellular automata[J]. Science in China Series D:Earth Sciences, 2005, 48(10):1758-1767.]
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