Abstract
Urban sprawl and space consumption have become key issues in sustainable territorial development. Traditional planning approaches are often insufficient to anticipate their complex spatial consequences, especially in cross-border areas. Such complexity requires the use of dynamic spatial simulations and the development of adapted tools like LucSim, a CA-based tool offering solutions for sharing spatial data and simulations among scientists, technicians and stakeholders. Methodologically, this tool allows us to simulate future land use change by first quantifying and then locating the changes. Quantification is based on Markov chains and location on transition rules. The proposed approach is implemented on the Strasbourg-Kehl cross-border area and calibrated with three contrasting prospective scenarios to try to predict cross-border territorial development.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Antoni JP (2006) Calibrer un modèled’évolution de l’occupation du sol urbain. L’exemple de Belfort.Cybergeo : Eur J Geogr. http://cybergeo.revues.org/2436
Antoni JP (2009) Un territoire de projet à co-construire. In: Grossouvre (de) H, Maulin E (eds) Euro-District Strasbourg-Ortenau : la construction de l’Europeréelle. Xénia, pp 25–31
Basse RM, Omrani H, Charif O et al (2014) Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale. Appl Geogr 53:160–171
Batty M, Xie Y (1994) From Cells to Cities. Environ Plan 21:531–538
Benenson I, Torrens PM (2004) Geosimulation: automata-based modeling of urban phenomena, 1st edition. Wiley
Berchtold A (1998) Chaînes de Markov etmodèles de transition. Hermes Science Publications, Paris, Applications aux sciences sociales
Clarke KC, Hoppen S, Gaydos L (1997) A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay Area. Environ Plan 24:247–261
Coplan DB (2012) Border Show Business and Performing States. In: Wilson TM, Donnan H (eds) A companion to border studies. Wiley-Blackwell, pp 507–521
Couclelis H (1985) Cellular Worlds: a framework for modeling micro-macro dynamics. Environ Plann A 20:99–109
Couclelis H (1987) Cellular dynamics: How individual decisions lead to global urban change. Eur J Oper Res 30:344–346
Couclelis H (2005) “Where has the Future Gone?” Rethinking the role of integrated land-use models in spatial planning. Environ Plann A 37:1353–1371
Durr MJ, Kayali ML (2014) Six millions d’habitants pour l’Alsace, Chiffres pour l’Alsace, 50
European Environment Agency (2006) Urban sprawl in Europe: the ignored challenge. EEA Report
Feller W (1968) An introduction to probability theory and its applications, 3rd edn. Wiley
Judge V, Antoni J-P, Klein O (2015) Land use simulation: statistical analysis approaches to calibrate cellular automata
Kaiser RJ (2012) Performativity and the Eventfulness of Bordering Practices. In: Wilson TM, Donnan H (eds) A companion to border studies. Wiley-Blackwell, pp 522–537
Kolossov V (2012) Euroborderscapes: State of the Debate, Report for the 7th Framework Programme of the European Commission
Koomen E, Hilferink M, Borsboom-Van Beurden J (2011) Introducing land use scanner. In: Koomen E, Borsboom-Van Beurden J (eds) Land-use modelling in planning practice. Springer, pp 3–21
Stoklosa K, Besier G (2014) European border regions in comparison: overcoming nationalistic aspects or re-nationalization?, 1st edn. Routledge, New York, London
Timmermans HJP (2003) The Saga of integrated land use-transport modeling: how many more dreams before we wake up? In: 10th International conference on travel behaviour research, Lucerne, Switzerland, p 35
Torrens PM (2000) How cellular models of urban systems work (1. theory). CASA Working Paper Series
Wegener M, Fürst F (1999) Land use transport interaction: state of the art. Transland, Irpud
White R, Engelen G (1993) Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environ Plann A 25:1175–1199
Acknowledgements
The research presented in this chapter is part of the Smart. Boundary project supported by the Fonds National de la Recherche in Luxembourg and CNRS in France (ref. INTER/CNRS/12/02). The authors would like also to thank the Grasp Program of LISER for allowing cross-collaboration between the two teams based in Luxembourg and France.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Antoni, J.P., Judge, V., Vuidel, G., Klein, O. (2018). Constraint Cellular Automata for Urban Development Simulation: An Application to the Strasbourg-Kehl Cross-Border Area. In: Camacho Olmedo, M., Paegelow, M., Mas, JF., Escobar, F. (eds) Geomatic Approaches for Modeling Land Change Scenarios. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-60801-3_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-60801-3_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60800-6
Online ISBN: 978-3-319-60801-3
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)