Koomen, E.

Rijken, B.C.

DSpace at VU

Applying and improving planning support 
systems for sustainable urban development 
Eric Koomen and Bart Rijken 
VU University Amsterdam, Department of Spatial Economics/SPINlab, 
De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands.  
PBL Netherlands Environmental Assessment Agency, PO Box 30314, 
2500 GH The Hague, The Netherlands. 
E-mail: e.koomen@vu.nl and b.c.rijken@vu.nl 
Land-use models have become an established tool to help prepare and sup-
port spatial planning. Typical examples concern the evaluation of policy 
alternatives and the exploration of future scenarios. This presentation de-
scribes three recent policy-related applications of an operational Dutch 
land-use model with a focus on sustainable urban development. Subse-
quently, it discusses ways to further improve land-use modelling in view 
of ongoing and expected changes in the societal and planning context of 
the Netherlands. 
The first example shows that a land-use model can successfully be used 
to depict likely outcomes of policy changes in a Strategic Environmental 
Assessment report dedicated to the newly proposed national spatial strat-
egy for the Netherlands. This what-if type of simulation typically relies 
strongly on expert judgement as it has to describe the impact of policies 
that have not yet been implemented and whose effects cannot be observed. 
These expert opinions can, to some extent, be tested in GIS-based analyses 
of the effectiveness of similar policies as described in other studies 
(Koomen et al., 2008). A recent, interview-based study by Van Kouwen 
(2012) into the potential future spatial developments in National Land-
scapes indicates that most parties involved do not expect sudden changes 
from the proposed changes in national spatial policy. These expectations, 
however, seem to be strongly linked to current political and economic 
conditions. When such conditions change, the current trend towards de-
regulation and decentralisation may lead to an increase in urban develop-
2      Eric Koomen and Bart Rijken 
ment in currently protected landscapes. Such threats to metropolitan open 
spaces have, for example, also been described by Van Rij (2009). There-
fore, we strongly believe that the type of scenario-based simulations of po-
tential impacts of policy changes described in this chapter offers a power-
ful approach to incorporate the notion of uncertainty in ex-ante policy 
evaluation. 
The second example shows that current ambition levels are needed to 
prevent extensive loss of open space. Should urban development (in terms 
of intensification share and extensions’ densities) follow past trends, large-
scale urban extensions are likely to occur. This is especially true when fu-
ture socio-economic conditions resemble the Global Economy scenario. 
Finally, the third case study shows that the Land Use Scanner can be a 
valuable tool in the field of climate adaptation as well. By simulating fu-
ture residential development at the highly detailed level of 1 hectare grid 
cells, it demonstrates that adaptation to flood risk emanating from future 
residential extension can be limited to highly localised strategies like spa-
tial zoning. Cost can be minimised by focusing local adaptation strategies 
on the areas where risk is most concentrated. Prioritising the places where 
these concentrations occur in more than one scenario enhances the robust-
ness of adaptation.  
Our simulations can easily be expanded to explore other scenarios or 
strategies, and accommodate additional spatial restrictions or other types 
of development (e.g. agriculture, industry/commerce, recreation). Such 
simulations have been performed as part of other studies focusing on, for 
example, the environmental impacts of a new regional strategic vision 
(Koomen et al., 2011) or the potential for new biofuels in the country 
(Kuhlman et al., 2013). 
The presented, recent Dutch land-use model applications focus on simu-
lating future urban expansion patterns. This is for many regions a very real 
scenario and Land Use Scanner is a powerful instrument to explore the 
impacts of new urban development in terms of, for example, loss of open 
space and flood risk. In the near future other spatial policy challenges may 
become prominent. These may relate to steering urban intensification in 
regions of urban growth and urban restructuring in regions of population 
decline (Kuijpers-Linde, 2011). Intensification has the potential to pre-
serve open space, keep down transportation costs, maximise urban eco-
nomic productivity etc. Effective restructuring, in turn, could minimise the 
damaging effect shrink may have on the economic health of urban areas.  
To allow the simulation of processes such as intensification and restruc-
turing we are currently busy incorporate residential land-use density in 
Land Use Scanner. Ultimately, this requires a distinction between actors 
(residents), objects (residences) and land use (residential land) and the ad-
Applying and improving planning support systems for sustainable urban 
development      3 
dition of information on each of these three layers in the model. Initial at-
tempts to incorporate residential density  have treated density change as 
exogenous model input, based on expert judgement and the extrapolation 
of past trends. This implies that, while all kinds of assumptions can be 
made regarding future dynamics on these issues, and numerous local indi-
cators can be derived from the resulting output, the underlying phenomena 
remain outside the model, preventing them to be simulated in an integrated 
way that is most probably require. Making these phenomena endogenous 
model parameters by incorporating the underlying mechanisms into the 
Land Use Scanner model would at once improve the explanatory power of 
the model regarding these highly relevant policy issues, and enhance the 
detail of the relevant model output (i.e., local density). This would greatly 
enhance the potential for subsequent impacts assessment such as local 
flood risk assessments discussed in the third example that was presented. 
Acknowledgements 
This research is funded by the research programme Urban Regions in the 
Delta (URD), part of the VerDuS-programme (‘Verbinding Duurzame 
Steden’) of the Netherlands Organisation for Scientific Research (NWO). 
We would like to thank PBL Netherlands Environmental Assessment 
Agency for providing the spatial data and land-use simulations that were 
incorporated in the analyses discussed in this chapter.  
References 
Koomen, E., Dekkers, J. and Van Dijk, T. (2008) Open-space preservation 
in the Netherlands: Planning, practice and prospects. Land Use 
Policy 25(3): 361-377.  
Koomen, E., Koekoek, A. and Dijk, E. (2011) Simulating Land-use 
Change in a Regional Planning Context. Applied Spatial Analysis 
and Policy 4(4): 223-247.  
Kuhlman, T., Diogo, V. and Koomen, E. (2013) Exploring the potential of 
reed as a bioenergy crop in the Netherlands. Biomass and 
Bioenergy doi: 10.1016/j.biombioe.2012.06.024.  
4      Eric Koomen and Bart Rijken 
Kuijpers-Linde, M. (2011) A policy perspective of the development of 
Dutch land-use models. Chapter 10. In: Koomen, E. and 
Borsboom-van Beurden, J. (eds.), Land-use modelling in planning 
practice. Springer, Heidelberg, pp. 177-189. 
Van Kouwen, M. (2012) Nationale Landschappen op de schop. 
Vernieuwing of achteruitgang? Bachelor thesis Earth and 
Economics. Vrije Universiteit, Amsterdam.  
Van Rij, E. (2009) Threats to metropolitan open space; The Netherlands 
economic and institutional dimension. Chapter 3. In: Van der 
Valk, A. and Van Dijk, T. (eds.), Regional planning for open 
space. Routledge, Abingdon, pp. 41-60. 
 
 


Applying and improving planning support systems for sustainable urban development

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VU Research PortalApplying and improving planning support systems for sustainable urban developmentKoomen, E.; Rijken, B.C.published inProceedings of CUPUM 20132013document versionPublisher's PDF, also known as Version of recordLink to publication in VU Research Portalcitation for published version (APA)Koomen, E., & Rijken, B. C. (2013). Applying and improving planning support systems for sustainable urbandevelopment. In S. Geertman, J. C. H. Stillwell, & F. Toppen (Eds.), Proceedings of CUPUM 2013 UtrechtUniversity.General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.            • Users may download and print one copy of any publication from the public portal for the purpose of private study or research.            • You may not further distribute the material or use it for any profit-making activity or commercial gain            • You may freely distribute the URL identifying the publication in the public portal ?Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.E-mail address:vuresearchportal.ub@vu.nlDownload date: 13. Sep. 2021Applying and improving planning support systems for sustainable urban development Eric Koomen and Bart Rijken VU University Amsterdam, Department of Spatial Economics/SPINlab, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands.  PBL Netherlands Environmental Assessment Agency, PO Box 30314, 2500 GH The Hague, The Netherlands. E-mail: e.koomen@vu.nl and b.c.rijken@vu.nl Land-use models have become an established tool to help prepare and sup-port spatial planning. Typical examples concern the evaluation of policy alternatives and the exploration of future scenarios. This presentation de-scribes three recent policy-related applications of an operational Dutch land-use model with a focus on sustainable urban development. Subse-quently, it discusses ways to further improve land-use modelling in view of ongoing and expected changes in the societal and planning context of the Netherlands. The first example shows that a land-use model can successfully be used to depict likely outcomes of policy changes in a Strategic Environmental Assessment report dedicated to the newly proposed national spatial strat-egy for the Netherlands. This what-if type of simulation typically relies strongly on expert judgement as it has to describe the impact of policies that have not yet been implemented and whose effects cannot be observed. These expert opinions can, to some extent, be tested in GIS-based analyses of the effectiveness of similar policies as described in other studies (Koomen et al., 2008). A recent, interview-based study by Van Kouwen (2012) into the potential future spatial developments i  National Land-scapes indicates that most parties involved do not expect sudden changes from the proposed changes in national spatial policy. These expectations, however, seem to be strongly linked to current political and economic conditions. When such conditions change, the current tr d towards de-regulation and decentralisation may lead to an increase in urban develop-2      Eric Koomen and Bart Rijken ment in currently protected landscapes. Such threats to metropolitan open spaces have, for example, also been described by Van Rij (2009). There-fore, we strongly believe that the type of scenario-based simulations of po-tential impacts of policy changes described in thisc apter offers a power-ful approach to incorporate the notion of uncertainty i  ex-ante policy evaluation. The second example shows that current ambition levels are needed to prevent extensive loss of open space. Should urban development (in terms of intensification share and extensions’ densities) follow past trends, large-scale urban extensions are likely to occur. This is especially true when fu-ture socio-economic conditions resemble the Global Economy scenario. Finally, the third case study shows that the Land Use Scanner can be a valuable tool in the field of climate adaptation as well. By simulating fu-ture residential development at the highly detailed level of 1 hectare grid cells, it demonstrates that adaptation to flood risk emanating from future residential extension can be limited to highly locaised strategies like spa-tial zoning. Cost can be minimised by focusing loca adaptation strategies on the areas where risk is most concentrated. Prioritis ng the places where these concentrations occur in more than one scenario enhances the robust-ness of adaptation.  Our simulations can easily be expanded to explore oth r scenarios or strategies, and accommodate additional spatial restrictions or other types of development (e.g. agriculture, industry/commerce, recreation). Such simulations have been performed as part of other studies focusing on, for example, the environmental impacts of a new regional str tegic vision (Koomen et al., 2011) or the potential for new biofuels in the country (Kuhlman et al., 2013). The presented, recent Dutch land-use model applications focus on simu-lating future urban expansion patterns. This is for many regions a very real scenario and Land Use Scanner is a powerful instrument to explore the impacts of new urban development in terms of, for example, loss of open space and flood risk. In the near future other spatial policy challenges may become prominent. These may relate to steering urban intensification in regions of urban growth and urban restructuring in regions of population decline (Kuijpers-Linde, 2011). Intensification has the potential to pre-serve open space, keep down transportation costs, maximise urban eco-nomic productivity etc. Effective restructuring, in turn, could minimise the damaging effect shrink may have on the economic health of urban areas.  To allow the simulation of processes such as intensification and restruc-turing we are currently busy incorporate residential land-use density in Land Use Scanner. Ultimately, this requires a distinction between actors (residents), objects (residences) and land use (residential land) and the ad-Applying and improving planning support systems for sustainable urban development      3 dition of information on each of these three layers in the model. Initial at-tempts to incorporate residential density  have treated density change as exogenous model input, based on expert judgement and he extrapolation of past trends. This implies that, while all kinds of assumptions can be made regarding future dynamics on these issues, and numerous local indi-cators can be derived from the resulting output, the underlying phenomena remain outside the model, preventing them to be simulated in an integrated way that is most probably require. Making these phenomena endogenous model parameters by incorporating the underlying mechanisms into the Land Use Scanner model would at once improve the explanatory power of the model regarding these highly relevant policy issues, and enhance the detail of the relevant model output (i.e., local density). This would greatly enhance the potential for subsequent impacts assessment such as local flood risk assessments discussed in the third example that was presented. Acknowledgements This research is funded by the research programme Urban Regions in the Delta (URD), part of the VerDuS-programme (‘Verbinding Duurzame Steden’) of the Netherlands Organisation for Scientific Research (NWO). We would like to thank PBL Netherlands Environmental Assessment Agency for providing the spatial data and land-use simulations that were incorporated in the analyses discussed in this chapter.  References Koomen, E., Dekkers, J. and Van Dijk, T. (2008) Open-space preservation in the Netherlands: Planning, practice and prospect. Land Use Policy 25(3): 361-377.  Koomen, E., Koekoek, A. and Dijk, E. (2011) Simulating Land-use Change in a Regional Planning Context. Applied Spatial Analysis and Policy 4(4): 223-247.  Kuhlman, T., Diogo, V. and Koomen, E. (2013) Exploring the potential of reed as a bioenergy crop in the Netherlands. Biomass nd Bioenergy doi: 10.1016/j.biombioe.2012.06.024.  4      Eric Koomen and Bart Rijken Kuijpers-Linde, M. (2011) A policy perspective of the development of Dutch land-use models. Chapter 10. In: Koomen, E. and Borsboom-van Beurden, J. (eds.), Land-use modelling in planning practice. Springer, Heidelberg, pp. 177-189. Van Kouwen, M. (2012) Nationale Landschappen op de schop. Vernieuwing of achteruitgang? Bachelor thesis Earth and Economics. Vrije Universiteit, Amsterdam.  Van Rij, E. (2009) Threats to metropolitan open space; The Netherlands economic and institutional dimension. Chapter 3. In: Van der Valk, A. and Van Dijk, T. (eds.), Regional planning for open space. Routledge, Abingdon, pp. 41-60.   

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Applying and improving planning support systems for sustainable urban development

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