1. Modeling Geographic Dispersion in an Urban Area ©2001 Nathan B. Forrester and Matthew S. Forrester

2. Background The Megapolis Project examined urban development patterns in Paris during 1990- 1991 The Megapolis model showed why a “multi-cellular” settlement pattern or distributed development poles make an urban area dysfunctional

3. Overview The Megapolis model simplifies and extends Urban Dynamics (Jay Forrester, 1969) Retained Concepts: –Jobs, Population, Business and Residential Structures –Attractiveness Principle New Concepts: –Geographical disaggregation –Commuting –Variable construction density

4. Structure –Large area divided into a grid of 49 squares –Key Stocks in each area: Jobs Residents Business and Residential Structures –Visibility of Jobs and Workers depends on commute time between areas –Jobs, Residents, and Businesses change depending on visibility, occupancy, and density

5. Scenarios to Follow Initial conditions for Jobs, Residents, and Structures: –Balanced on average for the city –Spread evenly over the entire area Sequence of structural additions –Each scenario adds a new feedback concept to the model

6. 49 Stocks 49 x 49 = 2401 Flows each for Jobs and Residents Basic Structural Unit

7. Generic Urban Grid

8. Scenario 1: Internal Movement due to Job/Worker Visibility –Activate internal movement of residents and jobs between areas in response to visibility of jobs and workers –Not yet activated: Net Migration in/out of city Construction Occupancy effects on movement Density effects on movement

9. Implosion –Limited commute tolerance makes jobs/residents on opposite sides of the city invisible to each other –High visibility of jobs and workers makes the center more attractive than the periphery –Residents and businesses implode toward the city center –Implosion ceases when most residents and jobs are all within an easy commute of each

10. People move to areas with higher job visibility

11. 400k 0 JobsResidents Scenario 1: Movement

12. Residents & Business

13. Scenario 2: Net In/Out Migration Structural Addition: –Positive feedback loop attracts people to the city due to high job visibility, further increasing visibility Behavioral change: –Exponential growth in total population proceeds in parallel with implosion to the city center

14. Attractiveness drives migration into and out of the city

15. 1.2M 0 JobsResidents Scenario 2: Migration

16. Scenario 3: Occupancy Limits Structural Addition: –Occupancy rates of residential and business structures impact attractiveness of an area Behavioral change: –Implosion stops abruptly as structures in the center become crowded and vacant structures on the periphery become attractive. –Total population declines

17. People move in response to differential occupancy rates

18. 400k 0 JobsResidents Scenario 3: Occupancy

19. Scenario 4: Construction Structural Addition: –Occupancy rates drives Net Construction of residential and business Structures Behavioral change: –Implosion implosion and exponential growth dominate again as occupancy constraints relax –Total population grows more slowly due to construction lags

20. Occupancy drives construction

21. 600k 0 JobsResidents Scenario 4: Construction

22. Scenario 5: Density Limits Structural Addition: –Density influences the attractiveness of an area Behavioral change: –Implosion and growth continue until the urban core becomes sufficiently crowded to constrain business or residential growth –Urban profile becomes flatter

23. Density retards growth

24. 400k 0 JobsResidents Scenario 5: Density

25. Scenario 6: Differential Density Structural Addition: –Businesses tolerate (or prefer) high density –Residents prefer living in low-density area Behavioral change: –Businesses crowd to the center –Residents spread out in a ring around the center –The city supports more people with lower unemployment

26. 400k 0 JobsResidents Scenario 6: Differential Density

27. Residents

28. Scenario 6: Differential Density Business

29. Policy Experiment 1: Improved Transit Parameter Change: –Time to travel a given distance drops Behavioral change: –The urban area expands horizontally –Population rises –In equilibrium, city is bigger, not better

30. Experiment 1: Transit Population v. Time: -Base -Transit

31. Population Profile: -Base -Transit Experiment 1: Transit

32. Attractiveness Profile: -Base -Transit

33. Policy Experiment 2: Central Zoning Constraints Parameter Change: –Zoning restricts permissible density of business construction density in core Behavioral change: –Businesses move out of the center –Most residents move further from the center –Some residents move back to urban core –Total unemployment rises

34. Experiment 2: Zoning Unemployment v. Time: -Base -Transit

35. 400k 0 JobsResidents Experiment 2: Zoning

36. Megapolis Simulator The Megapolis model is packaged in as a custom Venapp  Interface was written using an automatic code generator developed in Microsoft Excel Order a copy on the sign-up sheet

37. Megapolis Simulator Dashboard

38. Venapp  Code Generator