Modeling Geographic Dispersion in an Urban Area

©2001 Nathan B. Forrester andMatthew S. Forrester

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

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

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

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

49 Stocks49 x 49 = 2401 Flows each for Jobs and Residents

Basic Structural Unit

People(by Area)

MovementOut

MovementIn

NetMigration

Attractiveness

Generic Urban Grid

Layout of numbered urban cells

29 13 5 1 3 11 2736 20 9 4 8 17 3344 25 19 12 18 24 4149 43 35 28 34 42 48

37 21 6 2 7 16 3245 22 14 10 15 23 4046 38 30 26 31 39 47

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

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

People move to areas with higher job visibility

People(by Area)

MovementOut

MovementIn

NetMigration

Attractiveness

JobVisibiltity

-

400k 400k0

Jobs Residents

Scenario 1: Movement

Scenario 1: Movement

1

3

5

7S1

S2S3

S4S5

S6S7

0

100000

200000

300000

400000

Residents& Business

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

People(by Area)Net

Migration

Attractiveness

JobVisibiltity

City AvgAttractiveness to

ExteriorCity Job/LaborForce Balance

+

Attractiveness drives migration into and out of the city

1.2M 1.2M0

Jobs Residents

Scenario 2: Migration

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

People(by Area)

MovementOut

MovementIn

Attractiveness

Occupancy

Structures

-Net

Migration

People move in response to differential occupancy rates

400k 400k0

Jobs Residents

Scenario 3: Occupancy

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

People(by Area)

MovementOut

MovementIn

Attractiveness

Occupancy

Structures

NetConstruction

--

Occupancy drives construction

600k 600k0

Jobs Residents

Scenario 4: Construction

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

People(by Area)

MovementOut

MovementIn

NetMigration

Attractiveness

Density

-

Density retards growth

400k 400k0

Jobs Residents

Scenario 5: Density

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

400k 400k0

Jobs Residents

Scenario 6: Differential Density

Scenario 6: Differential Density

1

3

5

7

S1S2

S3S4

S5S6

S7

050000100000150000200000250000300000

Residents

1

3

5

7

S1S2

S3S4

S5S6

S7

050000100000150000200000250000300000

Scenario 6: Differential Density

Business

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

Experiment 1: Transit

Populationv. Time:

-Base-Transit

PopulationProfile:

-Base-Transit

Experiment 1: Transit

Experiment 1: Transit

AttractivenessProfile:

-Base-Transit

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

Experiment 2: Zoning

Unemploymentv. Time:

-Base-Transit

400k 400k0

Jobs Residents

Experiment 2: Zoning

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

Megapolis Simulator Dashboard

Venapp Code Generator