Session 1 - Montefiore

52
Annex: Data and methodological approach
subtracted from that area. The growth is expressed as
a percentage.
• Annual growth of built-up areas from the
mid-1950s to late 1990s (See above for definition).
Growth has been calculated for three time
periods:
1950s–1960s, 1960s–1980s and 1980s–1990s. It has
then been divided into an annual percentage.
• Share of low density residential areas compared
with all residential areas built after the mid-1950s.
In the MOLAND database the residential
areas have been classified into two main
categories: continuous and discontinuous. The
discriminating factor is density. If buildings and
other structures cover more than 80 % of the land,
the area is classified as continuous residential area
and if they cover less than 80 % it is classified as
discontinuous residential area. The threshold of
80 % has been used in this context as a boundary
between dense and low-density residential areas.
The indicator has been calculated by measuring
the extent of all residential areas built after the
1950s and low density residential areas built after
the 1950s. The share is the percentage of the latter
as compared with the former.
• The growth rate of residential, industrial,
commercial and transport areas (from the
mid-1950s to the end 1990s). The indicator has
been calculated by measuring the extent of
residential, industrial, commercial and transport
areas in the 1990s and comparing with the same
areas in the 1950s. Growth is expressed as a
percentage.
• City population and built up area growth from
1950s to 1990s. The population statistics have
been collected from municipal, regional and
national statistical offices. If a municipality is only
partially included in the MOLAND database,
the population figure for that municipality is
proportionally reduced.
• Residential density (measured by inhabitants/
residential km 2 ). The indicator has been calculated
by dividing the total number of the population by
the area of residential land use.
Development of scenarios (FORECAST):
Development of 'urban growth' scenarios for a sub-
Urban sprawl in Europe
set of the 25 cities, using state-of-the-art urban
cellular automata model.
The MOLAND urban growth model is based on
dynamic spatial systems called 'cellular automata'.
Inputs to the model are different types of spatially
referenced digital data including:
• Land use maps showing the distribution of
land use types in the area of interest. These
maps are derived from the MOLAND reference
and historical land use databases.
• Suitability maps showing the inherent
suitability of the area of interest for different
land use types. These maps are created using
an overlay analysis of maps of various physical,
environmental and institutional factors.
• Zoning maps showing the zoning status (i.e.
legal constraints) for various land uses in the
area of interest. These maps are derived from
existing planning maps e.g. master plans,
zoning plans, designated areas, protected
areas, historic sites, natural reserves, land
ownership.
• Accessibility maps showing accessibility to
transportation networks for the area of interest.
These maps are computed from the MOLAND
land use and transportation network databases,
based on the significance of access to transport
networks for the various land uses.
• Socio-economic data: for the main
administrative regions of the area of
interest, comprising demographic statistics
i.e. population and income, and data on
production and employment for the four main
economic sectors e.g. agriculture, industry,
commerce, and services.
The outputs from the MOLAND urban model
consist of maps showing the predicted evolution of
land use in the area of interest over the next twenty
years. By varying the inputs into the MOLAND
urban model e.g. zoning status, transport networks
etc, the model can be used as a powerful planning
tool to explore in a realistic way future urban and
regional development, under alternative spatial
planning and policy scenarios, including the
scenario of non-planning.