1. Bursts and avalanches in the dynamics of polycentric cities ENGINEERING LEADERSHIP BY SYSTEMS ENGINEERING 18 January, 2012 Danny Czamanski http://complexcity.csregistry.org/ Technion - Israel Institute of Technology 1

2. Activities in the lab Analyses of the joint dynamics of cities and nature: ISF funded project – joint dynamics of cities and nature; Lower Saxony funded project – joint dynamics of cities, agriculture and biodiversity; Multi-year, on-going inter-university workshop of faculty members and grad students. 2

3. Cities and Nature 3 Series Editors: Daniel Czamanski, Israel Institute of Technology (Coordinating Editor) Itzhak Benenson, Tel Aviv University Henk Folmer, University of Groningen Elena Irwin, The Ohio State University Czamanski, D., Benenson, I., Malkinson, D., (eds.) Modeling of Land-Use and Ecological Dynamics, Berlin, Springer International Publishers, signed contract, forthcoming in 2013 Czamanski, D., Benenson, I., Malkinson, D., Cities and Nature, Berlin, Springer International Publishers, signed contract, forthcoming in 2012

4. Our goal To depict and explain urban dynamics characterized by: Discontinuity in space; Non uniformity in time; Emergence of multiple sub-centers. 4

5. Motivation Dissatisfaction with classical urban models: Inability to generate polycentric spatial structures; Very limited dynamics; Accord with reality at a crude spatial resolution only. 5

6. Motivation Alonso type models: Focus on the demand-side; Depict spatial configuration once stable equilibrium has been achieved; Results in mono-centric cities. Real cities do not evolve as predicted by Alonso! 6

7. Motivation Cities are discontinuous in space and time Built area of Tel Aviv metropolis: 1935, 1941, 1952, 1964, 1974, 1985, 1993, 2000 7

8. Motivation Multiple high-rise buildings clusters Building heights distribution in Tel Aviv: 1972, 1986, 2003 8

9. New agent-based CA model… Both demand and supply are taken into account Much of the urban space dynamics and configuration may be explained by out-of-equilibrium situations Out-of-equilibrium opportunities for developers lead to outcomes difficult to explain under strictly stable equilibrium frameworks. 9

10. Assumptions Real-estate developers’ behavior is influenced by site specific parameters: Willingness to pay for real-estate products Land purchase price Characteristic time: Spans the time from the purchase of property rights until realization of a return 10

11. Previous Work Developer’s behavior in a linear space between two cities Profits are influenced by time incidence of costs and revenues… there are local maxima…developers’ location decisions create edge cities. Czamanski D., Broitman D. "Developers' choices under varying characteristic time and competition among municipalities". Annals of Regional Science 11

12. Two developers types: Impatient developers characterized by financial constraints and are therefore unable to wait long periods of time to realize a return of investment Patient developers have financial capabilities and can afford longer delay times risks in land purchase decisions. Assumptions 12

13. The playground: A square grid of cells (parcels) Cells attributes: Characteristic time Status Built height WTP Land price Dynamic model of sub-centers 13

14. Dynamic model of sub-centers City’s population grows steadily City policy: Characteristic time is a function of location and height Concentrated development around the CBD is preferred, but … Spatial policy adaptation 14

15. Dynamic model of sub-centers City planners: Monitor the city evolution by means of: Excess of demand (ED) Development pressure (P) Intervene if their combination is above a predefined “urbanization threshold” 15

16. Dynamic model of sub-centers City planners: Identify the cluster with maximal development pressure Change the local land use policy defining a low characteristic time circle around it 16

17. Dynamic model of sub-centers Each constructed building changes the WTP and the land price in its surroundings Developed high- building sites tend to attract more development in their surroundings 17

18. Impatient developers only Dynamic model of sub-centers 18

19. Mixed patient / impatient developers Dynamic model of sub-centers 19

20. Dynamic model of sub-centers A visual example of bursts creation and development pressure areas

21. Model results and Self Organizing Criticality (SOC) The SOC concept was coined in order to describe non- equilibrium systems which respond to an external perturbation with events of all sizes and no apparent characteristic scale. 21

22. Model results and SOC Our model dynamics and results resemble the SOC metaphor; A stable system, driven out of equilibrium by endogenous agents, causing bursts of activity of several sizes at unexpected times. 22

23. Model results and SOC 23

24. The bursts distribution has two well-defined ranges: 24 Patient developers only Bursts created by mixed developers

25. Model results and SOC The upper range represents the adversarial interaction between planning authorities and developers 25

26. Model results and SOC Interpreting “construction bursts” as “avalanches” leads to suggestive rank-size results: 26

27. Conclusions Characteristic time is important determinant of profitability levels Developers’ time aversion influences site and intensity choices Urban spatial structure reflects different types of developers Polycentric structure emerges as a result of developers’ choices A self-organizing system approaching a critical state ? 27