Decision Support Tools for Managing Urban Environment in Ireland

The MOLAND Model Calibration and Validation for

the Greater Dublin Region Dr Harutyun Shahumyan

harutyun.shahumyan@ucd.ie

University College Dublin

MOLAND Models at 3 coupled spatial scales

• Global level

Growth figures for the population and the

jobs are entered into the model as trend lines.

• Regional level

Arranges for the allocation of the Global

growth as well as for the interregional migration of activities and residence based on relative attractiveness of the counties.

• Local level

The detailed allocation of economic

activities and people is modelled by means of a Cellular Automata based land use model.

1926 1946 1956 1966 1979 1986 1996 2006

Population and Employment Trends

Transport Zones Accessibility

Suitability

Zoning

Land use map at time T

Land use map at time T+1

MICRO MODEL

Local Level (426,500 cells)

Neighbourhood Rules

Socio-Economic Information

Global Level (Greater Dublin Region)

Land Use Transition in MOLAND Model

Time step: 1 year

Regional Level (5 counties in the Region)

MACRO MODEL

Parameters Description

The attractivity of region i on sector k at time t

Population potential in sector k and region i at time t

Job potential in sector k and region i at time t

Activity potential in sector k and region i at time t

The productivity of sector k in region i at time t-1 (previous time step)

[unit: # people or jobs / cell]

The average neighbourhood effect of sector k in region i at time t

The average suitability of sector k in region i at time t

The average zoning of sector k in region i at time t

The average accessibility of sector k in region i at time t

,

t

k iVP

,

t

k iVJ

,

t

k iV

1

,

t

k iW

1

,

t

k iR

1

,

t

k iS

1

,

t

k iZ

1

,

t

k iA

1, 2, 3, 4, 6, 7, 8, 10,1 1 1 1 1

, , , , , , , , ,k k k k k k k kt t t t t t t t t

k i k i k i k i k i k i k i k i k iT VP VJ V W R S Z A

,

t

k iT

Macro Model: Interregional Attractivity

Parameters Description

CA transition potential of cell (x,y) for land use K

Scalable stochastic perturbation term

Suitability of cell (x,y) for land use K

Zoning of cell (x,y) for land use K

Accessibility of cell (x,y) for land use K at time t

Neighbourhood effect for cell (x,y) for land use K at time t

Micro Model: CA Transition Potential

4321

)()()()( ,,,,,,,,,,KKKK

yxK

t

yxK

t

yxK

t

yxK

t

yxK

t RAZSP

yxK

t P ,,

t

1

)( ,,K

yxKS

2

)( ,,K

yxK

tZ

3

)( ,,K

yxK

tA

4

)( ,,K

yxK

tR

1tv In rand

Sample MOLAND Simulation - Output

24 Land use classes

Suitability maps

In MOLAND the suitability values are expressed on a scale of 0 (completely unsuitable) to 10 (highly suitable), and are computed using:

• Slope map

• Aspect map

• Soil quality map

• Agricultural capacity

• Natural hazards maps

• Geomorphologic map

• Air, noise, water, soil

pollution maps

Zoning Maps

• The model uses a zoning raster file with binary cell values, namely, permitted (0) and not permitted (1). That is, zoning specifies whether a cell may or may not be taken over by a specific land use.

• 3 zoning periods are allowed: – Permitted throughout simulation period

– Permitted between time T1 and time T2

– Permitted between time T2 and time T3

• GDR zoning maps were developed based on special protection, conservation and national heritage areas.

Accessibility Maps

Accessibility maps capture the relative importance of access to the transportation networks for the various land uses: for example, activities like “commerce” require better accessibility than “agricultural use” in order to facilitate the supply and transport of goods and services.

Social-Economic Information

• Population counts by counties – Population censuses 1986, 1991, 1996, 2002 and 2006

• Place of work data by counties in 3 industrial groups (Industry, Commerce and Services) – POWSAR 2002, POWCAR 2006

– Occupation by place of residence data from CSO censuses 1991, 1996, 2002 and 2006

Calibration Procedure

• The macro and micro sub-models are decoupled and calibrated individually in the initial stages.

• In the first instance, the micro-model is calibrated.

• Next, the parameters of the macro-model are calibrated.

• In the final stages, they are coupled again and calibration carried out on the linked models.

Calibration Phases

NE

A

Z

S

P , J

NE

A

Z

S

P , J

NE

A

Z

S

P , J

1990

Calibration Validation Application

Macro Model Calibration Results (2000-2006 calibration)

Population Actual Value CSM (Error %) Simulated (Error %)

Base year 1990 1990 2000 1990 1990 2000

End Year 1990 2000 2006 2000 2006 2006 2000 2006 2006

Louth 90941 98603 111267 1.98% 0.77% -1.19% 6.93% 10.19% 3.14%

Meath 105072 125914 162831 -7.73% -20.44% -13.78% 4.41% -0.09% -3.17%

Dublin 1024533 1101302 1187176 2.87% 6.41% 3.44% -0.80% -0.71% 0.03%

Kildare 121374 154293 186335 -13.02% -19.69% -7.67% -5.96% -8.14% -2.52%

Wicklow 96720 110678 126194 -3.37% -5.50% -2.21% 5.06% 9.82% 4.76%

Total 1438641 1590790 1773803 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

RMSE 5.47% 11.47% 6.15% 2.31% 3.04% 1.24%

Macro Model Calibration Results (2000-2006 calibration)

Industry Actual Value CSM (Error %) Simulated (Error %)

Base year 1990 1990 2000 1990 1990 2000

End Year 1990 2000 2006 2000 2006 2006 2000 2006 2006

Louth 9669 13179 18236 2.50% -13.89% -15.99% 54.11% 46.74% 6.75%

Meath 9888 17285 31040 -20.08% -48.26% -35.27% 50.46% 13.14% -9.14%

Dublin 119521 156939 157445 6.40% 23.29% 15.87% -18.75% -15.59% 0.00%

Kildare 11934 22231 33626 -25.00% -42.36% -23.15% 32.50% 16.51% -0.33%

Wicklow 8959 13860 19453 -9.70% -25.20% -17.17% 45.84% 32.91% 8.84%

Total 159971 223494 259800 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

RMSE 12.08% 36.54% 24.71% 32.97% 23.79% 3.05%

Macro Model Calibration Results (2000-2006 calibration)

Commerce Actual Value CSM (Error %) Simulated (Error %)

Base year 1990 1990 2000 1990 1990 2000

End Year 1990 2000 2006 2000 2006 2006 2000 2006 2006

Louth 6101 9139 14970 -2.56% -23.55% -21.54% 47.38% 37.81% 6.53%

Meath 4555 8688 23693 -23.48% -63.94% -52.88% 112.84% 23.36% -7.74%

Dublin 148331 209911 234042 3.14% 18.88% 15.27% -16.10% -11.87% 0.00%

Kildare 6499 12826 29199 -26.05% -58.25% -43.55% 92.13% 31.89% 0.45%

Wicklow 6065 9822 19886 -9.87% -42.79% -36.53% 79.86% 36.53% 3.62%

Total 171551 250386 321790 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

RMSE 6.90% 35.14% 28.30% 34.10% 21.68% 1.53%

Macro Model Calibration Results (2000-2006 calibration)

Services Actual Value CSM (Error %) Simulated (Error %)

Base year 1990 1990 2000 1990 1990 2000

End Year 1990 2000 2006 2000 2006 2006 2000 2006 2006

Louth 5142 8310 12130 -11.28% -22.81% -13.00% 28.37% 29.81% 8.84%

Meath 3828 7284 17750 -24.64% -60.73% -47.89% 94.74% 26.41% -7.94%

Dublin 97013 133591 145888 4.12% 21.08% 16.28% -17.58% -14.59% 0.02%

Kildare 6395 10790 22539 -15.02% -48.34% -39.21% 73.93% 26.82% -3.95%

Wicklow 3864 6699 13349 -17.29% -47.30% -36.28% 93.26% 52.02% 8.99%

Total 116242 166673 211656 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

RMSE 8.32% 37.03% 28.75% 35.68% 25.29% 2.45%

Macro Model Calibration Results (1990-2006 calibration)

Population Industry Commerce Services

Base

year 1990 1990 2000 1990 1990 2000 1990 1990 2000 1990 1990 2000

End Year 2000 2006 2006 2000 2006 2006 2000 2006 2006 2000 2006 2006

Louth 2.4% 2.4% 0.7% 20.1% 7.2% -9.1% 16.4% -0.8% -9.8% 0.6% -6.9% -6.6%

Meath 8.2% 2.3% -3.2% 24.9% -4.8% -18.0% 61.9% -6.0% -25.6% 57.0% 0.1% -20.4%

Dublin -0.6% 0.0% 0.2% -7.2% 0.1% 7.4% -8.6% -0.2% 6.0% -9.1% -0.6% 6.1%

Kildare -7.5% -8.9% -2.3% 3.4% -10.0% -13.4% 57.6% 6.1% -12.2% 50.7% 6.8% -11.1%

Wicklow 5.0% 7.7% 4.7% 26.3% 17.3% 0.4% 39.5% 1.5% -15.3% 37.4% 1.1% -14.9%

RMSE 2.5% 2.5% 1.2% 13.0% 4.4% 11.9% 18.5% 1.6% 11.2% 19.1% 2.1% 10.7%

Micro Model Calibration Neighbourhood Rules

Distance rules representing

location preferences of land

uses in competition for space.

Commerce

Industry

Commerce

Water Residential Industry Commerce

In MOLAND these

are seen as

attraction and

repulsion

between land use

classes

Neighbourhood Rules Residential continuous dense urban fabric

on Commercial areas

Neighbourhood Rules Industrial areas on

Residential continuous urban fabric

Fuzzy Kappa Comparison Results

Low Agreement

MOLAND

Random Constraint

Match

Fuzzy Kappa 0.836 0.798

The Fuzzy kappa comparison method takes into account the similarities between land use classes by giving elements that correspond to similar categories higher weights.

The algorithm takes 2 kinds of fuzziness into account:

• category

• location

High Agreement

Running the Model Beyond 2006

Actual 2006 (left) and simulated 2026 (right) land use maps.

Cluster size – frequency plot of GDR 2050 land use map simulated by MOLAND

Running the Model Beyond 2006

Summary

MOLAND performs quite well in terms of regional estimates of population and activities, which compare favourably with actual estimates and constant share projections.

Fuzzy kappa comparisons and cluster size frequency plots also show that the model simulates realistic images of development trends and the spatial dynamics of the region.

It was decided that future work running simulations with the model will use the parameter values from the 2000-2006 calibration period. However, depending on the time period and context for simulations the other parameter values from the 1990 – 2006 calibration may also be considered.

However…

Issues and potential for future development

• Calibration was done in 2008 using 1990-2006 datasets

• Census 2011 provides updated socio-economic information

• Myplan.ie public information system provides data about the development plan or local area plans which can be used for more realistic zoning maps

• Suitability maps should be reviewed as the current maps obtained from JRC has no documentation about the sources and the methodology used

• There is a need for up to date land use map for GDR to carry on the recalibration

• Fully integrated transport model in the latest version

Thank You! www.uep.ie

The Urban Environment Project is generously sponsored by the Irish Environmental Protection Agency as part of the ERTDI programme which is funded through the National Development Plan. 2005-CD-U1-M1 “Decision support tools for managing urban environment in Ireland’ All work undertaken on the MOLAND model, for the Greater Dublin Region is subject to the license conditions of the software developers, Research Institute Knowledge Systems b.v. (RIKS b.v.) and the data set owners, DG JRC under license no. JRC.BWL.30715.

The author would like to acknowledge the valuable contribution of

Prof. Roger White and UEP team.