Computational Approaches for Urban Environments: An Editorial - Computational Approaches for Urban Environments - page 2

predict that the worldwide proportion of people living in urban environments will
double by 2030 compared to the 1950s. According to this trend, in Europe, for
instance, the percentage of the population living in urban areas increased from
1950 to 2007 from 42 to 72 %. More important is that this trend of urban growth
will continue within the next one or two decades. The United Nations forecast
that the European urban population will increase to more than 78 % until 2030.
Without doubt, these urbanization processes, due to their far-reaching impacts on
the economy, climate change, and health, among others, will intensify the pressure
on cities and urban societies even more. In order to be prepared for and to manage
these future challenges, well-thought-out planning and policy strategies are required
(Shafizadeh-Moghadam and Helbich 2015 ;Clarke 2014 ). In this regard, quantitative
modeling can add significantly to our understanding of how cities function. Equally
important is to undertake research linking cities with computational approaches and
put such research on policy agendas throughout the world.
As discussed by Pacione ( 2009 ), urban environments are highly multifaceted
areas consisting of several subcomponents, including housing markets (e.g., Helbich
et al. 2013a , c ), transportation systems (e.g., De Vos and Witlox 2013 ) etc., shaping
our cities across different scales. Each of these components comprises of its own
spatial and spatiotemporal patterns and processes. As indicated in Fig. 1.1 ,the
complexity is further amplified through interrelationships between these individual
components. For illustration purposes, let us examine the following example: We
assume that the accessibility of an urban fringe is improved by means of a highway
construction. Due to this new transportation infrastructure provision, the improved
linkage between the suburbs and the core city reduces commuting time and thus
makes these metropolitan outskirts more attractive for new residents to move in.
This accompanied increase in the demand for new residential areas results in
raising suburban land and housing prices, which makes residential land affordable
for higher-income classes, only. This rather simple example illustrates that the
components of urban environments are highly connected to each other and comprise
of interrelated feedback loops.
Although cities have been widely studied during the last decades and meticulous
research dealing with economical, infrastructural, environmental, political, social,
Fig. 1.1 Components of
urban environments