City of Jerez Urban Core Densification Proposal; An Agenda Based … · 2016-11-23 · City of Jerez Urban Core Densification proposal; An Agent Based Spatio-temporal model ... •Agent-based

City of Jerez Urban Core Densification proposal; An Agent Based Spatio-temporal model

Modelling urban population allocation

Elke Sauter

Julia Úbeda

Who we are & why we are here • Masters programme:

– Geographical Information Management and Applications (GIMA)

– Joint initiative between four Dutch Universities

• Broader context: Msc project as a pilot of a PhD

“Advanced planification model, new ICT and

their applicability in urbanism: Spatial

information, scenario simulation and impact

evaluation”- Irene Luque Irene Luque

Content

• Problem Definition

• Why to model?

• Question to be answered

• Agent-based modeling

• Modeling exercise: conceptualization and implementation

• Results, conclusions and discussion

3

Problem definition Why to model? R. Question ABM Modelling exercise Results & discussion

Problem Definition

5

Jerez de la Frontera


6

National Statistical Institute INE (Instituto Nacional de Estadística)

Demographics: 2013 - 2029


Where to accommodate this

incoming population?

Jerez Municipality drafted an Expansion Plan

7

Aiming to control the population allocation


What does expansion actually mean for a city like Jerez?

8

Source: byyourbesttraveler.com

• Huge investment in new infrastructure – higher taxes to pay by its citizens

• Degradation of valuable ecosystems and economic drivers in the region

• Loss of the sense of community + reduce liveability of the inner city


Alternative

Local Urban Planners, on behalf of citizens, support the densifying scenario – taking advantage of the

vacant space existing in the inner city

9 Problem definition Why to model? R. Question ABM Modelling exercise Results & discussion

Why to model?

Why to model? – What can be done?

11

Real necessity of making the solution visual & understandable


12

Leads to…

Informed Stakeholders

Municipality Jerez citizens

Better and supported decisions

Municipality

Why to model? – What can be done?


Research Question

Question to be answered: Expand or densify?

To what extent can the Jerez inner city accommodate the upcoming population?

AND

When should the city expansion plan be implemented to guarantee an optimal functioning of the existing city?

14

Timing WHEN?

Population allocation WHERE?

Circumstances HOW?


Agent Based Model

What is an agent?

single autonomous entity

expresses behavior by making decisions by taking actions

to meet their objectives

-Agarwal et al., 2002; Joffre et al., 2015

1


Agent-Based Modelling

A computational tool to simulate:

Complex systems in non-computing related scientific domains: biology, ecology & social science

Dynamically interacting components Emergence - can give rise to collective behavior -New England Complex Systems Institute (n.d.)


AB models for urban planning – in the frame of the PhD

• Heterogeneous stakeholders diverse opinions

• varying viewpoints

-Joffre et al. (2015)

• Behavior • Decision making processes

Complex systems:

-Salvini et al. (2016)

Contexts scenarios

B A

C


Gama

Uses the GAML agent-oriented programming language

Connects GIS-based data to populate the model

Enables ‘agentification’ capabilities for geo-data

Agent Geo-data

Census Units (CU)= agent

CU=neighborhood


Modelling exercise

Steps

5. Talk to lawmakers

4. Validate

3. Implementation

2. Urban indicators

1. Setting goals

Conceptualization


Urban Indicators of the Built Environment

Urban Indicators

Land Use Infrastructure

Mobility Population

“An indicator quantifies and aggregates data that can be measured and monitored to determine whether change is taking place” (FAO, 2002)


CU attractiveness as a force to pull people in

Attractiveness

to evaluate when

urban expansion plan should be put into effect

CU#1

CU Attractiveness scores

Level of data

aggregation


Combined CU Attractiveness

Score

Land Use Score Range

[1-5]

Population Score Range

[1-5]

Infrastructure Score Range

[1-5]

Mobility Score Range

[1-5]

Attractiveness Scores


Attractiveness Scores: Population

0

1

2

3

4

5

6

10 20 30 40 50 60 70 80 90 100

Sco

re

% Population

% Pop. Score

0-10 2

11-20 2.75

21-30 3.5

31-40 4.25

41-50 5

51-60 3.25

61-70 2.5

71-80 1.75

81-100 1


Attractiveness Scores: Land Use

Land Use Score

MIX 5

RES, PF, EA 3

Dynamic use of space by residents


Attractiveness Scores: Mobility

Attractiveness Scores: Infrastructure

Not implemented!


Agent-Based Model (Jerez Overview)

Censal Unit (CU)

Agent

Jerez City Boundary

Land Use

Mobility

Population

Infrastructure

Topology inside

Is a

Part of

Part of

Part of Part of

Part of

Environment

CU

Attributes


Initial Data

State Variables

Vacant Space

Maximum Population

Capacity of People Population

Built Residential

Surface

Capacity Level

Calculations

Living Area

User Input

To calculate pop. score

- CU level


66 m2 18 m2

Living Area

Japan Spain United States 35 m2

Living Area

-Jayantha & Hui, n.d.


50%

Capacity Level Measure of how much something can hold

Traffic jams Infrastructure (pipelines) max/ full Crowded & busy

Urban planners can influence city operational levels!

Capacity Level

100%

Free flow cars Infrastructure (pipelines) empty Lonely feel

10%


2. Check

Allocation Process Overview Year Pop.

2016 2870

2017 3216

… …

CU

max attractiveness score

not reached full capacity

# people allocated

incoming population

<

CU# 17 Score: 20

CU# 5

Score: 20

4. Recalculate attractiveness scores

5. Update CU capacity

Iteration t=n

year= 2017 3. Select CU + Allocate

If

1. Incoming Population **year= year+1

**if necessary


Results

Population Allocation


Results Table

Capacity Level

Year Expand

Pop. Leftover

70% 201X XX,XXX

80% 202X X,XXX

90% 202X X,XXX

100% 202X X

Capacity Level

Year Expand

Pop. Leftover

70% 2018 36,363

80% 2021 26,551

90% 2025 15,582

100% 2029 2,890

Capacity Level

Year Expand

Pop. Leftover

70% 201X XX,XXX

80% 202X X,XXX

90% 202X X,XXX

100% 202X X

Japan Spain United States 18 m2 35 m2 66 m2

Higher capacity + lower living area = densification


Original State Year 2015

Spain- Jerez -1

25

8 14.75

3

12.5

5

10.25

2

18

4

20

4

73

6


Spain- Jerez -2

Allocation: 70% Capacity Level Reached

Expand by year 2018

25

8 12.5

20

10

11

73

6


Allocation: 100% Capacity Level Reached

Expand by year 2029

Spain- Jerez -3

41

8

97

6


Conclusions & Discussion

Conclusions & Reflections

• Living area rule and capacity levels have high impacts on the model. • Capacity levels vs. attractiveness of CU’s:

• find equilibrium between the two • be aware of the risks you want to assume • determinant of when to expand

• Urban planners/ Municipality of Jerez to evaluate whether densification is a good policy to deal with the incoming population.

• Agent based model as a tool for modelling urban complex systems.


• Inclusion of other urban indicators for more holistic approach:

• mobility and infrastructure

• housing prices

• demographic characterization of agents and their preferences

• Evaluating sustainability (economic, environmental and social impacts)

• Methodology can be replicated with case specific parameters

Discussion and future work


Questions?

• Agarwal, C., Green, G. M., Grove, J. M., Evans, T. P., & Charles M. Schweik. (2002). A review and assessment of land-use change models: dynamics of space, time, and human choice, 1–61. Retrieved from http://www.geog.ucsb.edu/~kclarke/ucime/Helens-Sem/seminar2001/Land_Use_ Draft_9.pdf

• Food and Agriculture Organization of the United Nations (2002) Pressure-State-Response Framework and Environmental Indicators. Available from: http://www.fao.org/ag/againfo/ programmes/en/lead/toolbox/refer/envindi.html

• Joffre, O. M., Bosma, R. H., Ligtenberg, A., Tri, V. P. D., Ha, T. T. P., & Bregt, A. K. (2015). //***Combining participatory approaches and an agent-based model for better planning shrimp aquaculture. Agricultural Systems, 141, 149–159. http://doi.org/10.1016/j.agsy.2015.10.006

• Jayantha, W. M., & Hui, E. C. M. (n.d.). Central Europe towards Sustainable Building CESB10 Prague Assessment Methods DETERMINANTS OF HOUSING CONSUMPTION AND RESIDENTIAL CROWDING IN HONG KONG.

• New England Complex Systems Institute. (n.d.). About Complex Systems | NECSI. Retrieved April 21, 2016, from http://www.necsi.edu/guide/study.html

• Salvini, G., Ligtenberg, A., van Paassen, A., Bregt, A. K., Avitabile, V., & Herold, M. (2016). REDD+ and climate smart agriculture in landscapes: A case study in Vietnam using companion modelling. Journal of Environmental Management, 172, 58–70. http://doi.org/10.1016/j.jenvman.2015.11.060

Bibliography

Problem definition Question to asnwer Why to model? ABM Modelling exercise Results & discussion

Documents

City of Jerez Urban Core Densification Proposal; An Agenda Based … · 2016-11-23 · City of Jerez Urban Core Densification proposal; An Agent Based Spatio-temporal model ... •Agent-based