Transcript Kein Folientitel - Spiekermann & Wegener

Multi-scale spatial models:
linking macro and micro
Michael Wegener
Spiekermann & Wegener, Urban and Regional Research
Dortmund, Germany
Centre for Advanced Spatial Analysis
University College London
091 January 2008
Integrated land-use transport models
Today's integrated land-use transport models suffer from
several 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 environmental feedback is impossible.
- Issues of spatial equity cannot adequately be addressed.
2
PROPOLIS & ILUMASS
Microsimulation
New activity-based microsimulation models improve
urban 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.
3
Conclusions
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 interfaces between the submodels.
The feedback between transport and location and environmental 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.
4
Conclusions
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.
5
The Spitfire
6
The one-to-one model of the Spitfire
7
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)
8
Conclusions
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.
9
Conclusions
Macro or micro?
These considerations lead to a reassessment of the
hypothesis that eventually all spatial modelling will be
microscopic and agent-based.
10
Macro
or
micro?
11
??
Adapted from Miller et al., 1998.
Conclusions
Conclusions (1)
Only integrated microsimulation land-use transport models
models 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 terms
of data requirements and long computing times.
There are privacy concerns and ethical issues involved.
12
Conclusions
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 multiscale 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.
13
Multi-Scale Modelling
The Dortmund Example
14
Model levels
Multi-level
Dortmund City
Dortmund
Dortmund
Multi-scale
Regions
15
Zones
Raster cells
Level 1: Regions
16
Model levels
Dortmund City
Dortmund
Dortmund
Regions
17
Zones
Raster cells
SASI Model
Transport
policy
Production
function
18
Accessibility
Migration
function
GDP
Income
Population
Employment
Unemployment
Labour
force
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.
19
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
C3
20
A-1 Reference Scenario
Münster
Dortmund
Dortmund
Dortmund
Duisburg
Essen
Bochum
Dortmund
Hagen
Düsseldorf
Cologne
21
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:
22
Level 2: Zones
23
Model levels
Dortmund City
Dortmund
Dortmund
Regions
24
Zones
Raster cells
Study area
Hamm
Dortmund
Bochum
Hagen
Internal zones
External zones
25
Speed of change
Urban systems
Very slow
Networks
Goods transport
Travel
Employment
Population
Workplaces
Housing
Land use
26
Very fast
Fast
Slow
Very slow
Dortmund
model
Employment
Workplaces
from SASI model
Microsimulation
27
Labour
market
Population
households
Market for
nonresidential
buildings
Transport
market
Housing
market
Nonresidential
buildings
Land
market
Residential
buildings
Travel distance per capita per day (km)
28
Share of walking and cycling trips (%)
29
Share of public transport trips (%)
30
Share of car trips (%)
31
Average trip speed (km/h)
32
Car fuel consumption per car trip per traveller (l)
33
CO2 emission by transport per capita per day (kg)
34
Level 3: Raster Cells
35
Model levels
Dortmund City
Dortmund
Dortmund
Regions
36
Zones
Raster cells
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 environmental impact models (= reduced ILUMASS model).
37
Reduced
ILUMASS
model
from SASI model
Microsimulation
38
0 < 20 E/ha
20 < 40 E/ha
40 < 60 E/ha
60 < 80 E/ha
80 < 100 E/ha
100 < 120 E/ha
120 < 140 E/ha
140 < 160 E/ha
160 < 180 E/ha
39
180 < 200 E/ha
< 200 E/ha
Firms and households
Start
Start
Select a household
Select a firm
Check satisfaction with present
location
Satisfied?
Yes
Demographic events
- Ageing
- Death
- Birth
- Marriage/cohabitation
- Divorce/separation
- Persons leave household
- Persons move together
No
Select alternative location
No
1-10
Accept?
No
Economic events
- Education
- Place of work
- Employment status
- Income
- Mobility budget of household
11
Yes
Update lists
- Firms
- Nonresidential floorspace
- Employed persons
Yes
Another
firm?
Update lists
- Persons
- Households
- Dwellings
- Firms
Yes
Another
household?
No
40
End
No
End
Dwellings
Start
Expected demand
- Demolition
- Upgrading
- Construction
Select project
- Demolition
- Upgrading
- Construction
Select type and number of dwellings
Select type and number of dwellings
Select type and number of dwellings
Select zone and
microlocation
Select zone and
microlocation
Select zone and
microlocation
Demolition and resulting moves
Upgrading
Construction
Update lists
- Persons
- Households
- Dwellings
- Construction
Another
project?
41
No
End
Ye
s
Moves
Housing demand
Housing supply
Start
Start
Select dwelling
- Area
- Type
Select household
- Outmigration
- Immigration
- New household
- Move
Select household
- Immigration
- New household
- Forced move
- Move
Select dwelling
- Area
- Type
No
Accept?
1-5
No
6
1-5
Accept?
Yes
Yes
Update lists
- Households:
- with dwelling
- without dwelling
- Dwellings
- occupied
- vacant
Update lists
- Households:
- with dwelling
- without dwelling
- Dwellings
- occupied
- vacant
Yes
Another
household?
No
End
42
No
Yes
Another
dwelling?
No
End
No
6
Environmental
Impacts and Feedback
43
Model levels
Dortmund City
Dortmund
Dortmund
Regions
44
Zones
Raster cells
Environmental
feedback
No spatial
disaggregation
45
PROPOLIS
ILUMASS
Spatial disaggregation
of output
Spatial disaggregation
of input
Zonal data
Zonal data
Zonal data
Aggregate
Aggregate
land-usetransport
transport
land-use
model
model
Aggregate
Aggregate
land-usetransport
transport
land-use
model
model
Spatial
disaggregation
Zonal
environmental
impact model
Spatial
disaggregation
Microsimulation
land-use transport
model
Disaggregate
environmental
impact model
Disaggregate
environmental
impact model
Few impacts
Limited feedback
All impacts
Limited feedback
All impacts
All feedbacks
Net residential density (Zone)
Zone v. Raster
Density
46
Net residential density (Raster)
Percent open space (Zone)
Zone v. Raster
Open space
47
Percent open space (Raster)
Mean No2 emission (Zone)
Zone v. Raster
Air pollution
48
Mean No2 exposure (Raster)
Mean traffic noise (Zone)
Zone v. Raster
Traffic noise
49
Mean traffic noise exposure (Raster)
Reduced
ILUMASS
model
from SASI model
Microsimulation
Environmental impacts
50
Typical Model Run
51
Conclusions
Model dimensions
1.2 million
2.6 million
1.2 million
80,000
92,000
8,400
848
13,000
246/54
209,000
52
households
persons
dwellings
firms
industrial sites
public transport links
public transport lines
road links
internal/external zones
raster cells
30
simulation periods (years)
90
minutes computing time
Model parameters
53
Micro data
54
Travel flows
55
Travel flows
Public
transport
flows
56
Travel flows
57
Link loads
58
Public
Link
loads
transport
speed
59
Public
Link
loads
transport
speed
60
Air quality
NO2
61
Traffic noise
dB(A)
62
Firms
63
Households
64
Dwellings
Households
65
Vacant dwellings
66
Moves
Households
67
Compression
of micro data
68
Aggregation
to zones
69
Micro data
70
Simulation
completed
71
More information
Moeckel, 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.
72
73