Abstract
Co-evolutionary processes are according to the evolutionary urban theory at the center of urban systems dynamics. Their empirical observation or within models of simulation remains however relatively rare. This chapter is focused on the co-evolution of transportation networks and cities and applies high performance computing numerical experiments to the SimpopNet co-evolution model in order to understand its behavior. We introduce specific indicators to quantify trajectories of such models for systems of cities, and apply these to exhibit co-evolutionary regimes of the model. This illustrates how the systematic exploration of a simulation model can qualitatively transform the knowledge it provides.
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References
Achibet, M., Balev, S., Dutot, A., Olivier, D.: A model of road network and buildings extension co-evolution. Procedia Comput. Sci. 32, 828–833 (2014)
Arduin, H.: Modélisation mathématique des interactions entre pathogènes chez l’hôte humain: Application aux virus de la grippe et au pneumocoque. Ph.D. thesis, Université Paris-Saclay (2018)
Arthur, W.B.: Complexity and the shift in modern science. In: Conference on Complex Systems, Tempe, Arizona (2015)
Banos, A.: Pour des pratiques de modélisation et de simulation libérées en géographie et shs. Ph.D. thesis, Université Paris 1 Panthéon Sorbonne (2013)
Banos, A.: Knowledge accelerator’ in geography and social sciences: further and faster, but also deeper and wider. In: Urban Dynamics and Simulation Models, pp. 119–123. Springer (2017)
Baptiste, H. (2010). Modeling the evolution of a transport system and its impacts on a French urban system. In: Graphs and Networks: Multilevel Modeling, 2nd edn, pp. 67–89
Batty, M.: Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. The MIT Press (2007)
Benenson, I., Torrens, P.M.: Geosimulation: object-based modeling of urban phenomena. Comput. Environ. Urban Syst. 28(1–2), 1–8 (2004)
Bird, I.: Computing for the large hadron collider. Annu. Rev. Nucl. Part. Sci. 61, 99–118 (2011)
Blumenfeld-Lieberthal, E., Portugali, J.: Network cities: a complexity-network approach to urban dynamics and development. In: Geospatial Analysis and Modelling of Urban Structure and Dynamics, pp. 77–90. Springer (2010)
Brasebin, M., Chapron, P., Chérel, G., Leclaire, M., Lokhat, I., Perret, J., Reuillon, R.: Apports des méthodes d’exploration et de distribution appliquées à la simulation des droits à bâtir. In: Spatial analysis and geomatics 2017 (2017)
Bretagnolle, A.: Vitesse et processus de sélection hiérarchique dans le système des villes françaises. Données Urbaines 4 (2003)
Bretagnolle, A.: Villes et réseaux de transport: des interactions dans la longue durée, France, Europe, États-Unis (HDR). Université Panthéon-Sorbonne, Paris I (2009, June)
Chérel, G., Cottineau, C., Reuillon, R.: Beyond corroboration: strengthening model validation by looking for unexpected patterns. PLoS ONE 10(9), e0138212 (2015)
Cottineau, C., Reuillon, R., Chapron, P., Rey-Coyrehourcq, S., Pumain, D.: A modular modelling framework for hypotheses testing in the simulation of urbanisation. Systems 3(4), 348–377 (2015)
Cottineau, C., Raimbault, J., Le Texier, M., Le Néchet, F., Reuillon, R.: Initial spatial conditions in simulation models: the missing leg of sensitivity analyses? In: 2017 International Conference on Geocomputation: Celebrating 21 Years of Geocomputation (2017)
Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press (2006)
Galam, S.: Sociophysics: a review of galam models. Int. J. Mod. Phys. C 19(03), 409–440 (2008)
LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436 (2015)
Liao, T.W.: Clustering of time series data—a survey. Pattern Recogn. 38(11), 1857–1874 (2005)
Mantegna, R.N., Stanley, H.E.: Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge University Press, Cambridge (1999)
Mimeur, C., Queyroi, F., Banos, A., Thévenin, T.: Revisiting the structuring effect of transportation infrastructure: an empirical approach with the French Railway Network from 1860 to 1910. Hist. Methods J. Quant. Interdisc. Hist. 51, 65–81 (2017)
Passerat-Palmbach, J., Reuillon, R., Leclaire, M., Makropoulos, A., Robinson, E.C., Parisot, S., Rueckert, D.: Reproducible large-scale neuroimaging studies with the openmole workflow management system. Front. Neuroinform. 11, 21 (2017)
Paulus, F.: Coévolution dans les systèmes de villes: Croissance et spécialisation des aires urbaines françaises de 1950 à 2000. Ph.D. thesis, Université Panthéon-Sorbonne-Paris I (2004)
Pumain, D.: Pour une théorie évolutive des villes. L’Espace Géographique 119–134 (1997)
Pumain, D.: Une théorie géographique des villes. Bull. Soc. Géogr. Liège 55, 5–15 (2010)
Pumain, D.: Les effets structurants ou les raccourcis de l’explication géographique. Espace Géogr. 43(1), 65–67 (2014)
Pumain, D., Reuillon, R.: Evaluation of the SimpopLocal model. In: Urban Dynamics and Simulation Models, pp. 37–56. Springer, Cham (2017a)
Pumain, D., Reuillon, R.: Urban Dynamics and Simulation Models. Springer International (2017b)
Raimbault, J.: For a cautious use of big data and computation. In: Royal Geographical Society-Annual Conference 2016-Session: Geocomputation, The Next 20 Years (1) (2016a)
Raimbault, J.: Génération de données synthétiques corrélées. In: Rochebrune 2016, journées d’Etude sur les systèmes complexes naturels et artificiels (2016b)
Raimbault, J.: An applied knowledge framework to study complex systems. In: Complex Systems Design & Management, pp. 31–45 (2017a)
Raimbault, J.: Identification de causalités dans des données spatio-temporelles. In: Spatial analysis and geomatics 2017 (2017b)
Raimbault, J.: Models coupling urban growth and transportation network growth: an algorithmic systematic review approach. Plurimondi (17) (2017c)
Raimbault, J.: An urban morphogenesis model capturing interactions between networks and territories. In: The Mathematics of Urban Morphology, pp. 383–409. Birkhäuser, Cham (2019)
Raimbault, J.: Calibration of a density-based model of urban morphogenesis. PloS. One. 13(9), e0203516 (2018a)
Raimbault, J.: Indirect evidence of network effects in a system of cities. Environ. Plann. B Urban Anal. City Sci. 2399808318774335 (2018b)
Raimbault, J.: Modeling the co-evolution of cities and networks. ArXiv E-Prints (2018c)
Raimbault, J.: Characterizing and modeling the co-evolution of transportation networks and territories. Theses, Université Paris 7 Denis Diderot (2018d). Retrieved from https://tel.archives-ouvertes.fr/tel-01857741
Raimbault, J., Banos, A., Doursat, R.: A hybrid network/grid model of urban morphogenesis and optimization. In: 4th International Conference on Complex Systems and Applications, pp. 51–60 (2014)
Reuillon, R., Leclaire, M., Rey-Coyrehourcq, S.: OpenMOLE, a workflow engine specifically tailored for the distributed exploration of simulation models. Future Gener. Comput. Syst. 29(8), 1981–1990 (2013)
Reuillon, R., Schmitt, C., De Aldama, R., Mouret, J.-B.: A new method to evaluate simulation models: the calibration profile (cp) algorithm. J. Artif. Soc. Soc. Simul. 18(1), 12 (2015)
Scarpino, S.V., Petri, G.: On the predictability of infectious disease outbreaks (2017). arXiv Preprint arXiv:1703.07317
Schamp, E.W.: 20 on the notion of co-evolution in economic geography. In: The Handbook of Evolutionary Economic Geography, p. 432 (2010)
Schmitt, C.: Modélisation de la dynamique des systèmes de peuplement: De simpoplocal à simpopnet. Ph.D. thesis, Université Panthéon-Sorbonne-Paris I (2014)
Wal, A.L.J.T., Boschma, R.: Co-evolution of firms, industries and networks in space. Reg. Stud. 45(7), 919–933 (2011)
Acknowledgements
Results obtained in this paper were computed on the vo.complex-system.eu virtual organization of the European Grid Infrastructure (http://www.egi.eu). We thank the European Grid Infrastructure and its supporting National Grid Initiatives (France-Grilles in particular) for providing the technical support and infrastructure. This work is part of DynamiCity, a FUI project funded by BPI France, Auvergne-Rhône-Alpes region, Ile-de-France region and Lyon metropolis. This work was also funded by the Urban Dynamics Lab grant EPSRC EP/M023583/1.
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Raimbault, J. (2020). Unveiling Co-evolutionary Patterns in Systems of Cities: A Systematic Exploration of the SimpopNet Model. In: Pumain, D. (eds) Theories and Models of Urbanization. Lecture Notes in Morphogenesis. Springer, Cham. https://doi.org/10.1007/978-3-030-36656-8_14
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DOI: https://doi.org/10.1007/978-3-030-36656-8_14
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