Cost benefit analysis of peri-urban land use policy - Plurel

The MOLAND Model
The MOLAND Model is a state-of-the-art land use model used widely in the EU and has been applied
to an extensive number of cities and regions such as Plurel study areas providing the methodology
for the impact evaluation of a wide variety of policies. The most important feature of the model is the
application of cellular modelling to the land cover which is named as cellular automata (CA). The CA
is based on a variety of inputs to determine the state of the land use in each cell according to a set of
transition rules representing the compatibility of land-uses with each other. Petrov et.al. (2009)
stated that the model is an improved version of the CA first developed by White et.al. (1997) and
achieved robustness through the successful applications in European Region and some other areas.
Among them, we can refer to the Dublin Metropolitan Area and other areas in Plurel region.
At the regional level, there are four sub-models utilised in MOLAND and identified as: (a) regional
economic sub-model which calculates sector production and employment followed by a spatial
allocation among the regions, (b) regional demographic sub-model calculates the growth of regional
population and allocates the regions housing demand, (c) transportation sub-model which is a fourstage
model calculating the changes in traffic flows and the resultant impacts on land-use
accessibility and inter-regional distances, (d) land-claim sub-model which translates the regional
socio-economic growth numbers into a spatial representation for a further detailed allocation at the
cellular (local) level (see Engelen et.al. 2007).
The model developed for Dublin Area has two components including regional and urban land-use
sub-models. The model includes an extensive data set covering the years 1990, 2000 and 2006 and
utilises both macro and micro-type parameters. Macro-level data such as GDP and population
growth are inputs for the regional sub-model, also affecting the urban land-use sub-model which is
run through a CA model. Since the data incorporated in this model came from a disaggregated data
set, the micro-model parameters i.e. neighbourhood effects, accessibility, zoning, population,
employment indicators etc. can be utilised to explain the micro-level spatial issues, which diverge the
model from those incorporating aggregate data sets and rely on large geographic districts.
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