Modeling dynamic urban growth using cellular automata and particle swarm optimization rules

Landscape and Urban Planning

Volumn 102, Issue 3, 2011, Pages 188-196

  Feng, Yongjiu ^a   Liu, Yan ^b   Tong, Xiaohua ^c   Liu, Miaolong ^c   Deng, Susu ^d  

^a SHANGHAI OCEAN UNIVERSITY   (China)

^b UNIVERSITY OF QUEENSLAND   (Australia)

^c TONGJI UNIVERSITY   (China)

^d HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Cellular automata; Dynamic modeling; Particle swarm optimization; Transition rules; Urban growth

Indexed keywords

CELLULAR AUTOMATA; DYNAMIC MODELS; PARTICLE SWARM OPTIMIZATION (PSO); ROBOTS; UNCERTAINTY ANALYSIS;

BOTTOM UP APPROACH; PARTICLE SWARM OPTIMIZERS; SELF ORGANIZATIONS; SIMULATION ACCURACY; SIMULATION UNCERTAINTY; SPATIAL RESOLUTION; SPATIO TEMPORAL; TRANSITION RULE;

URBAN GROWTH;

ACCURACY ASSESSMENT; CELLULAR AUTOMATON; MODEL TEST; OPTIMIZATION; PARAMETERIZATION; PERFORMANCE ASSESSMENT; SPATIAL RESOLUTION; SPATIOTEMPORAL ANALYSIS; STOCHASTICITY; UNCERTAINTY ANALYSIS; URBAN GROWTH;

CHINA; FENGXIAN; SHANGHAI;

EID: 80955177140     PISSN: 01692046     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.landurbplan.2011.04.004     Document Type: Article

References (52)

1. Al-kheder S., Wang J., Shan J. Fuzzy inference guided cellular automata urban growth modelling using multi-temporal satellite images. International Journal of Geographical Information Science 2008, 22(11):1271-1293.
2. Almeida C.M., Batty M., Monteiro A.M.V., Camara G., Soares-Filho B.S., Cerqueira G.C., et al. Stochastic cellular automata modeling of urban land use dynamics: Empirical development and estimation. Computers Environment and Urban Systems 2003, 27:481-509.
3. Almeida C.M., Gleriani J.M., Castejon E.F., Soares-Filho B.S. Using neural networks and cellular automata for modelling intra-urban land-use dynamics. International Journal of Geographical Information Science 2008, 22(9):943-963.
4. Andries P.E. Fundamentals of computational swarm intelligence 2006, Wiley, Hoboken.
5. Barredo J.I., Kasanko M., McCormick N., Lavalle C. Modelling dynamic spatial processes: Simulation of urban future scenarios through cellular automata. Landscape and Urban Planning 2003, 64:145-160.
6. Batty M., Xie Y. From cells to cities. Environment and Planning B-Planning & Design 1994, 21:531-548.
7. Batty M., Xie Y. Possible urban automata. Environment and Planning B-Planning & Design 1997, 24:175-192.
8. Batty M., Xie Y., Sun Z. Modeling urban dynamics through GIS-based cellular automata. Computers Environment and Urban Systems 1999, 23:205-233.
9. Campbell J.B. Introduction to remote sensing 1987, The Guilford Press, New York.
10. Clarke K.C., Gaydos L.J. Loose-coupling of a cellular automaton model and GIS: Long-term growth prediction for the San Francisco and Washington/Baltimore. International Journal of Geographical Information Science 1998, 12:699-714.
11. Clarke K.C., Hoppen S., Gaydos L. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B-Planning & Design 1997, 24:247-261.
12. Cohen J. A coefficient of agreement for nominal scale. Educational and Psychological Measurement 1960, 20:37-46.
13. Couclelis H. Cellular worlds: A framework for modelling micro-macro dynamics. Environment and Planning A 1985, 17(5):585-596.
14. Dragićević S., Marceau D.J., Marois C. Space, time, and dynamics modeling in historical GIS databases: A fuzzy logic approach. Environment and Planning B-Planning & Design 2001, 545-562.
15. Eberhart R.C., Shi Y. Comparison between genetic algorithms and particle swarm optimization. Lecture Notes in Computer Science 1998, 1447:611-616.
16. Gong J.Z., Liu Y.S., Xia B.C., Zhao G.W. Urban ecological security assessment and forecasting based on a cellular automata model: A case study of Guangzhou, China. Ecological Modelling 2009, 220:3612-3620.
17. Han J., Hayashi Y., Cao X., Imura H. Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai, China. Landscape and Urban Planning 2009, 91(3):133-141.
18. He C., Okada N., Zhang Q., Shi P., Li J. Modelling dynamic urban expansion processes incorporating a potential model with cellular automata. Landscape and Urban Planning 2008, 86:79-91.
19. He C., Okada N., Zhang Q., Shi P., Zhang J. Modelling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing. China. Applied Geography 2006, 26:323-345.
20. João P.P., Leila M.G., Fonseca, Lino A.S.C. Projections onto convex sets through particle swarm optimization and its application for remote sensing image restoration. Pattern Recognition Letters 2010, 31(13):1876-1886.
21. Kennedy J., Eberhart R.C. Particle swarm optimization. IEEE international conference on neural networks 1995, 1942-1948.
22. Kocabas V., Dragićević S. Assessing cellular automata model behaviour using a sensitivity analysis approach. Computers Environment and Urban Systems 2006, 30:921-953.
23. Kuo R.J., Lin L.M. Application of a hybrid of genetic algorithm and particle swarm optimization algorithm for order clustering. Decision Support Systems 2010, 49(4):451-462.
24. Landis J., Zhang M. The second generation of the California urban futures model. Part 1. Model logic and theory. Environment and Planning B-Planning & Design 1998, 25(5):657-666.
25. Li L., Sato Y., Zhu H. Simulating spatial urban expansion based on a physical process. Landscape and Urban Planning 2003, 64:67-76.
26. Li X., He J.Q., Liu X.P. Ant intelligence for solving optimal path-covering problems with multi-objectives. International Journal of Geographical Information Science 2009, 23(7):839-857.
27. Li X., Yang Q.S., Liu X.P. Discovering and evaluating urban signatures for simulating compact development using cellular automata. Landscape and Urban Planning 2008, 86(2):177-186.
28. Li X., Yang Q., Liu X. Genetic algorithms for determining the parameters of cellular automata in urban simulation. Science in China Series D: Earth Sciences 2007, 50:1857-1866.
29. Li X., Yeh A.G.O. Neural-network based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science 2002, 16(4):323-343.
30. Li X., Yeh A.G.O. Urban simulation using principal components analysis and cellular automata for land-use planning. Photogrammetric Engineering and Remote Sensing 2002, 68(4):341-351.
31. Liu X.P., Li X., Liu L., He J.Q., Ai B. A bottom-up approach to discover transition rules of cellular automata using ant intelligence. International Journal of Geographical Information Science 2008, 22(11):1247-1269.
32. Liu Y. Modelling urban development with geographical information systems and cellular automata 2008, CRC Press, New York.
33. Liu Y., Phinn S.R. Modelling urban development with cellular automata incorporating fuzzy-set approaches. Computers Environment and Urban Systems 2003, 27:637-658.
34. Maurice C. Particle swarm optimization 2007, ISTE Ltd., London.
35. Parunak H.V.D., Brueckner S.A., Matthews R., Sauter J. Swarming methods for geospatial reasoning. International Journal of Geographical Information Science 2006, 20(9):945-964.
36. Pérez L., Dragićević S. ForestSimMPB: A swarming intelligence and agent-based modeling approach for mountain pine beetle outbreaks. Ecological Informatics 2011, 6:62-72.
37. Pontius R.G., Huffaker D., Denman K. Useful techniques of validation for spatially-explicit land-change models. Ecological Modelling 2004, 179(4):445-461.
38. Santé I., García A.M., Miranda D., Crecente R. Cellular automata models for the simulation of real-world urban processes: A review and analysis. Landscape and Urban Planning 2010, 96:108-122.
39. Shi Y., Eberhart R.A. A modified particle swarm optimizer. Lecture Notes in Computer Science 1998, 1447:591-600.
40. Stevens D., Dragićević S. A GIS-based irregular cellular automata model of land-use change. Environment and Planning B-Planning & Design 2007, 34:708-724.
41. Stevens D., Dragićević S., Rothley K. iCity: A GIS-CA modelling tool for urban planning and decision making. Environmental Modelling & Software 2007, 22:761-773.
42. Sui D.Z., Zeng H. Modeling the dynamics of landscape structure in Asia's emerging Desakota regions: A case study in Shenzhen. Landscape and Urban Planning 2001, 53:37-52.
43. Tobler W.R. A computer movie simulating urban growth in the Detroit Region. Economic Geography 1970, 46:234-240.
44. Verburg P.H., Soepboer W., Limpiada R., Espaldon M.V.O., Sharifa M.A., Veldkamp A. Modelling the spatial dynamics of regional land use: The CLUE-S model. Environmental Management 2002, 30:391-405.
45. White R., Engelen G. Cellular automata and fractal urban form: A cellular modeling approach to the evolution of urban land-use patterns. Environment and Planning A 1993, 25:1175-1199.
46. White R., Engelen G. High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Computers Environment and Urban Systems 2000, 24:383-400.
47. Wu B., Cai L.A. Spatial modeling: Suburban leisure in Shanghai. Annals of Tourism Research 2006, 33(1):179-198.
48. Wu F. A linguistic cellular automata simulation approach for sustainable land development in a fast growing region. Computers Environment and Urban Systems 1996, 20(6):367-387.
49. Wu F. SimLand: A prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. International Journal of Geographical Information Science 1998, 12(1):63-82.
50. Wu F. Calibration of stochastic cellular automata: The application to rural-urban land conversions. International Journal of Geographical Information Science 2002, 16(8):795-818.
51. Wu F., Webster C.J. Simulation of land development through the integration of cellular automata and multi-criteria evaluation. Environment and Planning B-Planning & Design 1998, 25:103-126.
52. Xie Y. A generalized model for cellular urban dynamics. Geographical Analysis 1996, 28:350-373.