Multi-scale spatial models: linking macro and micro Michael Wegener

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Multi-scale spatial models:linking macro and micro

Michael WegenerSpiekermann & Wegener, Urban and Regional ResearchDortmund, Germany

Centre for Advanced Spatial AnalysisUniversity College London09 January 2008

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Integrated land-use transport models

Today's integrated land-use transport models suffer fromseveral weaknesses:- Their classification of households and individuals is too

crude; individual lifestyles cannot be represented.- Their transport models are not activity-based and cannot

address "soft" transport policies.- Their spatial resolution is too coarse to take account of

small-scale local policies.- Forecasting environmental impacts such as air pollution,

land take and traffic noise is difficult, modelling environ-mental feedback is impossible.

- Issues of spatial equity cannot adequately be addressed.

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Microsimulation

New activity-based microsimulation models improveurban simulation models:

- Individual lifestyles can be represented, households and individuals are disaggregated to the agent level.

- Environmental impacts can be modelled with the required spatial resolution.

- Environmental feedback between environment and land use and transport can be modelled.

- Microlocations can be represented. Households affected by environmental impacts can be localised.

PROP

OLIS

& IL

UMAS

S

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However ...

To date, no full-scale microsimulation model of urban land use, transport and environment has become operational.

There are still unresolved problems regarding the inter-faces between the submodels.

The feedback between transport and location and environ-mental quality and location has not yet been implemented.

Serious problems of calibration, stability and stochastic variation have not been solved.

The computing time for existing models is calculated in terms of weeks or days, not hours.

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How much micro is enough?

Despite these problems, microsimulation modellers engage in ever more ambitious plans to further raise the complexity and spatial resolution of their models.

The common belief among most microsimulation modellers seems to be: the more micro the better.

This is the dream of the one-to-one Spitfire.

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The Spitfire

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The one-to-one model of the Spitfire

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The one-to-one Spitfire

"Simplifying assumptions are not an excrescence on model-building; they are its essence. Lewis Carroll once remarked that a map on the scale of one-to-one would serve no purpose. And the philosopher of science Russell Hanson noted that if you progressed from a five-inch balsa wood model of a Spitfire air plane to a 15-inch model without moving parts, to a half-scale model, to a full-size entirely accurate one, you would end up not with a model of a Spitfire but with a Spitfire".

Robert M. Solow (1973)

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How much micro is enough?

There seems to be little consideration of the benefits and costs of microsimulation:

- Where is microsimulation really needed?

- What is the price for microsimulation?

- Would a more aggregate model do?

For spatial planning models, the answer to these questions depends on the planning task at hand.

For instance, for modelling the impacts of transport on land use, much simpler travel models are sufficient.

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Macro or micro?

These considerations lead to a reassessment of the hypothesis that eventually all spatial modelling will be microscopic and agent-based.Co

nclu

sions

11 Adapted from Miller et al., 1998.

Macro or micro?

??

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Conclusions (1)

Only integrated microsimulation land-use transport modelsmodels permit the modelling of - "soft" and local planning policies- individual lifestyles - environmental impacts and feedback- microlocations and spatial equity.

However, there is a price for the microscopic view in termsof data requirements and long computing times.

There are privacy concerns and ethical issues involved.

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Conclusions (2)

Under constraints of data collection and of computing time, there is for each planning problem an optimum level of conceptual, spatial and temporal resolution.

This suggests to work towards a theory of balanced multi-scale models which are as complex as necessary for the planning task at hand and as simple as possible but no simpler.

Future urban models will be modular and multi-scale in scope, space and time.

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Multi-Scale ModellingThe Dortmund Example

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Model levels

Dortmund

Regions

Dortmund

Zones

Dortmund City

Raster cells

Multi-level

Multi-scale

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Level 1: Regions

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Model levels

Dortmund

Regions

Dortmund

Zones

Dortmund City

Raster cells

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SASI Model

GDP

AccessibilityProductionfunction

Employment

Migrationfunction

PopulationIncome

Labourforce

Transportpolicy

Unemploy-ment

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The STEPs Project (2004-2006)

The EU 6th RTD Framework project STEPs (Scenarios for the Transport System and Energy Supply and their Potential Effects) developed and assessed possible scenarios for the transport system and energy supply of the future.

In the project five urban/regional models were applied to forecast the long-term economic, social and environmental impacts of different scenarios of fuel price increases and different combinations of infrastructure, technology and demand regulation policies.

Here the model results for the urban region of Dortmund, Germany, will be presented.

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The STEPs Project: Scenarios

The project developed a set of scenarios assuming different rates of energy price increases with three sets of policies:

Fuel price increase

+1% p.a. +4% p.a. +7% p.a.

Do-nothing A-1 B-1 C-1

Business as usual A0 B0 C0

Infrastructure & technology A1 B1 C1

Demand regulation A2 B2 C2

All policies A3 B3 C3A-1 Reference Scenario

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DortmundDortmund

Dortmund

Dortmund

Cologne

Hagen

Düsseldorf

Münster

EssenDuisburg Bochum

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Economic impacts for the Dortmund region

According to the SASI model, the fuel price increases and related policies of the scenarios have significant negative impacts on the economy of the Dortmund urban region:

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Level 2: Zones

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Model levels

Dortmund

Regions

Dortmund

Zones

Dortmund City

Raster cells

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Internal zones

External zones

Dortmund

Hamm

Hagen

Bochum

Study area

26E

n v i r o n m e n t

r b a nU

Urban systems

Networks

Travel

Population

Workplaces

Land use

Housing

Very fast

Fast

Slow

Very slow

Very slow

Goods transport

Employment

Speed of change

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Dortmundmodel

Microsimulation

from SASI model

Populationhouseholds

Nonresidentialbuildings

Residentialbuildings

EmploymentWorkplaces

Housingmarket

Transportmarket

Market fornonresidential

buildings

Land market

Labourmarket

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Travel distance per capita per day (km)

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Share of walking and cycling trips (%)

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Share of public transport trips (%)

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Share of car trips (%)

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Average trip speed (km/h)

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Car fuel consumption per car trip per traveller (l)

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CO2 emission by transport per capita per day (kg)

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Level 3: Raster Cells

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Model levels

Dortmund

Regions

Dortmund

Zones

Dortmund City

Raster cells

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The ILUMASS Project (2001-2006)

The project ILUMASS (Integrated Land-Use Modelling and Transport Systems Simulation) embedded a microscopic dynamic simulation model of urban traffic flows into a comprehensive model system incorporating both changes of land use and the resulting changes in transport demand as well as their environmental impacts.

For testing the land use submodels, the transport and environmental submodels were replaced by the aggregate transport model of the IRPUD model and simpler envir-onmental impact models (= reduced ILUMASS model).

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ReducedILUMASSmodel

Microsimulation

from SASI model

Microsimulation

from SASI model

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0 <

20 <

40 <

60 <

80 <

100 <

120 <

140 <

160 <

180 <

<

20 E/ha

40 E/ha

60 E/ha

80 E/ha

100 E/ha

120 E/ha

140 E/ha

160 E/ha

180 E/ha

200 E/ha

200 E/ha

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Firms and householdsStart

End

Another household?

Yes

No

Select a household

Demographic events- Ageing- Death- Birth- Marriage/cohabitation- Divorce/separation- Persons leave household- Persons move together

Economic events- Education- Place of work- Employment status- Income- Mobility budget of household

Update lists- Persons- Households- Dwellings- Firms

Start

End

Anotherfirm?

Yes

No

Select a firm

Select alternative location

Accept?No No

1-10 11

Yes

Update lists- Firms- Nonresidential floorspace- Employed persons

Check satisfaction with present location

Satisfied?

No

Yes

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Dwellings

Another project?

End

No

Update lists- Persons- Households- Dwellings- Construction

Yes

Select zone and microlocation

Select type and num-ber of dwellings

Upgrading

Select zone and microlocation

Select type and num-ber of dwellings

Demolition and result-ing moves

Select zone and microlocation

Select type and num-ber of dwellings

Construction

Start

Expected demand- Demolition- Upgrading- Construction

Select project- Demolition- Upgrading- Construction

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MovesStart

End

Another dwelling?

Yes

No

Select dwelling- Area- Type

Select household- Immigration- New household - Forced move- Move

Accept?No No

Update lists- Households: - with dwelling - without dwelling- Dwellings - occupied - vacant

1-5

Housing supply

Yes

Start

End

Anotherhousehold?

Yes

No

Select household- Outmigration- Immigration- New household- Move

Select dwelling- Area- Type

Accept?No No1-5 6

Yes

Housing demand

Update lists- Households: - with dwelling - without dwelling- Dwellings - occupied - vacant

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Environmental Impacts and Feedback

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Model levels

Dortmund

Regions

Dortmund

Zones

Dortmund City

Raster cells

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Environmental feedback PROPOLIS ILUMASS

Aggregate land-use transport model

Zonal data

Aggregate land-use transport model

Zonal environmental impact model

Aggregate land-use transport model

Zonal data

Aggregate land-use transport model

Spatial disaggregation

Zonal data

Microsimulationland-use transportmodel

Disaggregateenvironmental impact model

Disaggregateenvironmental impact model

No spatial disaggregation

Spatial disaggregationof output

Spatial disaggregationof input

Few impactsLimited feedback

All impactsLimited feedback

All impactsAll feedbacks

Spatial disaggregation

46 Net residential density (Raster)

Net

resi

dent

ial d

ensi

ty (Z

one)

Zone v. RasterDensity

47 Percent open space (Raster)

Per

cent

ope

n sp

ace

(Zon

e)

Zone v. RasterOpen space

48 Mean No2 exposure (Raster)

Mea

n N

o 2 e

mis

sion

(Zon

e)

Zone v. RasterAir pollution

49 Mean traffic noise exposure (Raster)

Mea

n tra

ffic

nois

e (Z

one)

Zone v. RasterTraffic noise

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Reduced ILUMASSmodel

Microsimulation

from SASI model

Microsimulation

from SASI model

Environmental impacts

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Typical Model Run

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Model dimensions

1.2 million households 2.6 million persons 1.2 million dwellings 80,000 firms 92,000 industrial sites

8,400 public transport links 848 public transport lines 13,000 road links

246/54 internal/external zones 209,000 raster cells

30 simulation periods (years)

90 minutes computing time

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Model parameters

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Micro dataMicro data

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Travel flows

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Public transportflowsTravel flows

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Travel flowsTravel flows

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Link loadsLink loadsLink loads

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Link loadsLink loadsLink loadsPublic transportspeed

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Link loadsLink loadsLink loadsPublic transportspeed

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Air quality NO2

62

Traffic noisedB(A)

63

FirmsFirmsFirmsFirmsFirmsFirms

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HouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholdsHouseholds

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HouseholdsDwellingsHouseholdsDwellingsHouseholdsDwellingsHouseholdsDwellings

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Vacant dwellings

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HouseholdsMovesMovesMovesMovesMoves

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Compression of micro data

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Aggregationto zones

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Micro dataMicro data

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Simulationcompleted

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More informationMoeckel, R., Schwarze, B., Spiekermann, K., Wegener, M. (2007): Simulating interactions between land use, transport and environment. Proceedings of the 11th World Conference on Transport Research. Berkeley, CA: University of California at Berkeley.

Wagner, P., Wegener, M. (2007): Urban land use, transport and environmental models: Experiences with an integrated microscopic approach. disP 43(170):45–56.

Wegener, M. (1998): The IRPUD Model: Overview. http://www. raumplanung.uni-dortmund.de/irpud/pro/mod/mod_e.htm.

Wegener, M. (2007): After the Oil Age: Do we have to rebuild our cities? Presentation at the SOLUTIONS Conference, University College London, 11-12 July 2007. http://www.suburbansolutions. ac.uk/sitemapdocs.aspx.

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