Design Implications of Model-Generated Urban Data

Main Article Content

Ljubomir Jankovic

Abstract

The staggering complexity of urban environment and long timescales in the causal mechanisms prevent designers to fully understand the implications of their design interventions. In order to investigate these causal mechanisms and provide measurable trends, a model that partially replicates urban complexity has been developed. Using a cellular automata approach to model land use types and markets for products, services, labour and property, the model has enabled numerical experiments to be carried out. The results revealed causal mechanisms and performance metrics obtained in a much shorter timescale than the real-life processes, pointing to a number of design implications for urban environments.

Article Details

How to Cite
Jankovic, L. “Design Implications of Model-Generated Urban Data”. Enquiry The ARCC Journal for Architectural Research, Vol. 16, no. 2, Nov. 2019, pp. 50 -63, doi:10.17831/enq:arcc.v16i2.1061.
Section
Peer Reviewed Papers

References

Batty, Michael. 2007. Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. 1. paperback ed. Cambridge, Mass.: MIT Press.
Jankovic, Ljubomir. 2012. ‘An Emergence-Based Approach to Designing’. The Design Journal 15 (3): 325–46. https://doi.org/10.2752/175630612X13330186684150.
Koutitas, G., N. Pavlidou, and L. Jankovic. 2010. ‘A Comparative Study of Two Alternative Wildfire Models, with Applications to WSN Topology Control’. In FOREST FIRES 2010, 25–36. Kos, Greece. https://doi.org/10.2495/FIVA100031.
Langton, C. 1992. ‘Life at the Edge of Chaos’. In Artificial Life II: Proceedings of the Workshop on Artificial Life: Held February 1990 in Santa Fe, New Mexico. Redwood City, Calif: Addison-Wesley.
Langton, Christopher G., ed. 1989. Artificial Life: The Proceedings of an Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems, Held September, 1987, in Los Alamos, New Mexico. Santa Fe Institute Studies in the Sciences of Complexity, v. 6. Redwood City, Calif: Addison-Wesley Pub. Co., Advanced Book Program.
von Neumann, John. 1951. ‘The General and Logical Theory of Automata.’ In Cerebral Mechanisms in Behavior; the Hixon Symposium., 1–41. Oxford, England: Wiley.
———. 1967. ‘Theory of Self-Reproducing Automata. John von Neumann. Edited by Arthur W. Burks. University of Illinois Press, Urbana, 1966. 408 Pp., Illus. $10’. Science 157 (3785): 180–180. https://doi.org/10.1126/science.157.3785.180.
Schelling, Thomas C. 1971. ‘Dynamic Models of Segregation†’. The Journal of Mathematical Sociology 1 (2): 143–86. https://doi.org/10.1080/0022250X.1971.9989794.
Shannon, C. E. 1948. ‘A Mathematical Theory of Communication’. Bell System Technical Journal 27 (3): 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
Wilson, A.G. 1967. ‘A Statistical Theory of Spatial Distribution Models’. Transportation Research 1 (3): 253–69. https://doi.org/10.1016/0041-1647(67)90035-4.
Wilson, Alan. 2018. ‘The Future of Urban Modelling’. Applied Spatial Analysis and Policy 11 (4): 647–55. https://doi.org/10.1007/s12061-018-9258-6.
Wolfram, Stephen. 2002. A New Kind of Science. Wolfram Media. https://www.wolframscience.com.