Simulating Urban Growth and Residential Segregation through Agent-Based Modeling

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MARETTO, R. V.; ASSIS, T. O.; GAVLAK, A. A. Simulating Urban Growth and Residential Segregation through Agent-Based Modeling. In: BRAZILIAN WORKSHOP ON SOCIAL SIMULATION, 2., , São Bernardo do Campo. Proceedings... Los Alamitos: IEEE, 2010. p. 52 - 57. DVD. ISBN 978-0-7695-4471-7, 978-1-4577-0895-4. doi: .

Transcript of Simulating Urban Growth and Residential Segregation through Agent-Based Modeling

Simulating Urban Growth and Residential Segregation through Agent-

Based Modeling

Raian Vargas Maretto¹Talita Oliveira Assis²

André Augusto Gavlak¹

¹ {gavlak, raian}@dpi.inpe.br²{talitaoliveiraassis}@gmail.com

Residential segregation

Objective• The purpose of this work is to replicate three classical models of urban

segregation through the simulation of the individual behavior of agents ina city.

KohlBurgessHoyt

Comprehend how Agent Based Modeling can be useful to replicate classical urban growth and urban segregation and models

Kohl

City Center

Low-income residential areas

Medium-income residential areas

High-income residential areas

Thompson, J.K.J. (1983) “Variations in industrial structure in pre-industrial Languedoc”, inBerg, Maxine, Hudson, Pat, and Sonenscher, Michael, Manufacture in town and countrybefore the factory, Cambridge: Cambridge University Press, 61-91.19th century

Kohl generalized the way social groups weredistributed inside the pre-industrial cities ofcontinental Europe

1920’s

Burgess

City Center

Low-income residential areas

Medium-income residential areas

High-income residential areas

Hoyt

City Center

Low-income residential areas

Medium-income residential areas

High-income residential areas

Calgary, Canada - 1969

Smith, P.J. (1962) "Calgary: A study in urban pattern",Economic Geography, 38(4), pp.315-329

According to the American economist Hoyt(1939), spatial segregation did not used toassume a circle pattern around the center, butspatial sectors originating from there.

Methodology – The environment9

9 c

ells

99 cells

Dwelling unit

Can contein an agent – Household

Low income – 50%

High income – 25%

Medium income – 20%

Financial agent (commerce, industry and services) – 5 %

City starts from the central cell – SEED

One agent inserted at each iteraction – Random class

Methodology – Hierarchy

Financial Agents

High Income Agents

Medium Income Agents

Low Income Agents

Methodology – Model Dynamics

Attempts to allocate the agent in cell

Choose neighborrandomly

Expels agent and takes place in cell

Insert newagent

Takes placein cell

Does newagent have

priority?

Emptycell?

N N

Y

Y

Expelle

d agen

t

Methodology – Hoyt ModelHigh-Income Agents

Low-Income AgentsMedium-Income Agents

Source: (CARNEIRO, 2006)

TerraME: Terra Modeling EnvironmentA development plataform for spatially-explicit dynamical modeling

TerraME: Concepts Components

Spatial structure: Nested CA

1:32:00 Mens. 11.

1:32:10 Mens. 32.

1:38:07 Mens. 23.

1:42:00 Mens.44.

. . .return value

true

1. Get first pair 2. Execute the ACTION

3. Timer =EVENT

4. timeToHappen += period

Temporal structure

Newly implanted

Deforesting

Slowing down

latency > 6 years

Iddle

Year of creation

Deforestation = 100%

Agents Modeling Generalised Spatial relations

Source: [Carneiro, 2006]

TerraME: Architecture

Source: (CARNEIRO, 2006)

Simulation results – Kohl

Simulation results - Burgess

Simulation results – Hoyt

Concluding Remarks

Next step use of real data

Agent‐based model was proved to be a suitable tool toreproduce urban growth and urban Residential Segregationmodels.

Methodology makes possible to replicate other models of this kindof phenomena.

TerraME has shown to be an powerful tool to implement thesemodels

Thank You!

Questions?