Cellular automata in the context of dynamic modeling: challenges in modeling urban areas

Authors

DOI:

https://doi.org/10.11606/eISSN.2236-2878.rdg.2021.181171

Keywords:

Dynamic Space Models, Spatial Simulation Models, Cellular Automata, Postgis.

Abstract

The science of solving spatially arranged problems has been modified from new scientific paradigms, concepts and innovations in progress. The systemic approach allowed, especially in Geography, the creation of models as tools that can significantly contribute to the understanding of terrestrial phenomena and assist in decision making. Models can be classified in different ways and according to their approach. In the field of dynamic modeling, there is a great challenge to structure models capable of portraying the diversity of objects and actions that are modified in space and time, a great challenge, especially in urban areas. In this sense, this article seeks to build a theoretical-conceptual review highlighting the use of different approaches based on the challenges and potential found in its use for the modeling of urban spaces. The integration of different spatial interactions and the need to incorporate them with the temporal dimension is translated into the use of cellular automata as a procedure capable not only of portraying the phenomena more faithfully, but also of associating short-term responses and predicting what would be the possible trajectories and results of proposed interventions in scenarios such as: what if? In this way, the use of cellular automata is analyzed, their historical approach and how they are included today in geographic information systems. Initiatives of this nature bring new perspectives to geographic studies, helping to understand the actions that are underway and that may generate the most different types of scenarios.

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References

ALMEIDA, C. M. de. Modelagem da dinâmica espacial como uma ferramenta auxiliar ao planejamento: simulação de mudanças de uso da terra em áreas urbanas para as cidades de Bauru e Piracicaba (SP), Brasil. 2003. 351f. Tese Instituto de Pesquisas Espaciais, São José dos Campos, 2003.

BATTY, M. 1976. Urban modelling: algorithms, calibrations, predictions. Cambridge, UK: Cambridge University Press.

BATTY, M. Generating urban forms from diffusive growth Environ. Plann. A, 23 (4) (1991), pp. 511-544

BATTY, M; LONGLEY. P.A. Fractal Cities Academic Press, London (1994)

BONHAM-CARTER, G. F. Geographic Information Systems for Geoscientists: Modelling with GIS. 2.ed. Kindlington: Pergamon Press, 1996. 400 p.

BURROUGH, P. and A. FRANK (ed.). Geographic Objects with Indeterminate Boundaries. London, Taylor; Francis, 1996.

CAPRA, F. A teia da vida: uma nova compreensão científica dos sistemas vivos. Tradução: Newton Roberval Eichemberg. Editora CULTRIX. São Paulo, 1996.

CARVALHO, G. Cenários Futuros para Cidades Inteligentes. 1ª ed. São Paulo – Trilha de Treinamentos e Consultoria, 193p. 2019.

CHRISTOFOLETTI, A. As perspectivas dos estudos geográficos. In: CHRISTOFOLETTI, A. (Ed.). Perspectivas da Geografia. São Paulo: Difel, 1985.

CLARKE, K.C.; GAYDOS, L.J.; Loose-coupling a cellular automaton model andGIS : long-term urban growth prediction for San Francisco and Washington/Baltimore int.j. geographical information science,1998, vol.12, no.7. 699-714.clarklabs. org, 2012.

CLARKE, K.C. S. HOPPEN, L. GAYDOS A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay área Environ. Plann. B: Plann. Design, 24 (1997), pp. 247-261.

COUCLELIS, H. Cellular worlds: a framework for modeling micro-macro dynamics. data.International Journal of Remote Sensing, v. 10 n. 06, pp. 989-1003. (1985)

COUCLELIS, H. (1997). “From Cellular Automata to Urban Models: New Principles for Model Development and Implementation.” Environment and Planning B: Planning and Design 24.

CORRÊA, R. L. O espaço urbano. São Paulo: Editora Ática, 1989.

GOMES, P.C.C. CASTRO, I.E., CORRÊA, R.L. Geografia: Conceitos e Temas. Rio de Janeiro, Ed. Bertrand Brasil, 2000. 352 p.

GOMEZ B.; JONES III, J.P. (2010) Research Methods in geography. ISBN 97814051-070-5.

HAGGETT, P.; CHORLEY, R. J. Models, paradigms and the new Geography. In: CHORLEY, R. J.; HAGGETT, P. (Ed.). Models in Geography. Londres: Methuen e Co., 1967. p. 19-41.

HAINES-YOUNG, R. H. AND PETCH, J. H. 1986. Physical geography: its nature and methods. London: Harper & Row.

HARGROVE W.W. et al., 2000. Simulating fire patterns in heterogeneous landscapes. Ecological Modelling. (135): 243-263.

INKPEN, R. Science, Philosophy and Physical Geography. 2005.

KILBRIDGE, M. D., O’BLOCK, R. P. AND TEPLITZ, P. V. Urban Analysis. Boston: 1970. Harvard

KUHN, T. S. A estrutura das revoluções científicas. 2. ed. São Paulo: Perspectiva, 1978.

LAMBIN, E. F. Modeling Deforestation Processes - A Review, Trees series B: Research Report (1994). European Commission, Luxembourg.

LÉVY, P. 1998, Cyberculture. Odile Jacob, France.

LIU, Y. Modelling Urban Development with Geographical Information Systems and Cellular Automata. CRC Press, Boca Raton, Florida, 2009. 204p.

LONGLEY, P. A. GOODCHILD, M.F., MAGUIRE, D.J. RHIND.D.W., Sistemas e Ciência da Informação Geográfica. 3. ed. Porto Alegre: Bookman, 2013. 560p.

LONGLEY. P.A MESEV, V. On the measurement and generalisation of urban form Environ. Planning A. A (2000) volume 32, pages 473-488. DOI:10.1068/a3224

MARTIN, D. Geographic information systems: socioeconomic applications. 2. Ed. London: Routledge, 1996. 210 p.

MENEZES, P. M. L.; FERNANDES, M. C. Roteiro de Cartografia. São Paulo: Oficina de textos, 2013

NOVAES, A. G. Modelos em planejamento urbano, regional e de transportes. São Paulo: Editora Edgard Blücher, 1981.

PEDROSA, B.M.; CÂMARA, G. Modelagem dinâmica e geoprocessamento. In: FULKS, S.D.; CARVALHO.M. S; CÂMARA, G.; MONTEIRO, A.M.V., eds. (2002) Análise Espacial de dados geográficos. INPE, Instituto Nacional de Pesquisas Espaciais

ROBINSON, G. M. 1998. Methods and techniques in human geography. New York: John Wiley.

SIRAKOULIS, G.C.; KARAFYLLIDIS, I.; THAINAILAKIS, A. 2000. A cellular automaton model for the effects of population movement and vaccination on epidemic propagation. Ecological Modelling (133): 209-223

SANTÉ I, et al., (2010) Cellular automata models for the simulation of real-world urban processes: a review and analysis. Landsc Urban Plan 96(2):108–122

SOARES-FILHO et. al. DINAMICA – a stochastic cellular automata model designed to simulate the ladscape dynamics in an Amazonian colonization frontier. Elsevier – ecological modelling 154 (2002) 217 – 235.

SOARES-FILHO, B. S., CERQUEIRA, G. C., ARAÚJO, W. L., AND VOLL, E. “Modelagem de dinâmica de paisagem: concepção e potencial de aplicação de modelos de simulação baseados em autômato celular.” Megadiversidade 3 (2007): 74-86.

SOARES-FILHO, B.S.; ASSUNÇÃO, R.M. PANTUZZO, A. 2001. Modeling the spatial transition probabilities of landscape dynamics in an Amazonian Colonization frontier. BioScience, (51): 1 039-1 046

TOBLER, W. Cellular geography. In: Philosophy in geography. Dordrecht: D. Reidel University. v. 51, n. 12, p. 1059-1067, 2001.

WOLFRAM, S. “Statistical mechanics of cellular automata”. Review of modern physics, v. 55, p.601-643, 1983.

WU, F. Calibration of stochastic cellular automata: the application to rural–urban land conversions Int. J. Geogr. Inform. Sci., 16 (8) (2002), pp. 795-818.

WHITE,R. G. ENGELEN Cellular dynamics and GIS: modelling spatial complexity Geogr. Syst., 1 (1994), pp. 237-253.

XIE, Y. A generalized model for cellular urban dynamics Geogr. Anal., 28 (1996), pp. 350-373.

YEH, A.G.O. et al., Cellular Automata Modeling for Urban and Regional Planning. In:Urban Informatics. BATTY, M. GOODCHILD, M.F.SHI, W. editors. Springer. 2021

Published

2021-06-21

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Artigos

How to Cite

Viégas, V. S., Cruz, C. B. M., & Souza, E. M. F. da R. de . (2021). Cellular automata in the context of dynamic modeling: challenges in modeling urban areas . Revista Do Departamento De Geografia, 41(1), e181171 . https://doi.org/10.11606/eISSN.2236-2878.rdg.2021.181171