Travel Reference
In-Depth Information
other elements in the system. This has made it especially useful, for example, in identifying
the wilderness attributes of an area and the effects of developments on wilderness values such
as naturalness (Carver
et al.
, 2002; Machado, 2004; Hall and Page, 2006), as well as as a tool
for site management (Lang and Langanke, 2005). The dynamic element of GIS also allows
future scenarios and forecasts to be spatially visualised. For example, Marshall and Simpson
(2009) combined GIS with forecasting methods to explore issues of population sustainability
in the UK's Cairngorms and Peak District National Parks.
Simulation has become an increasingly important planning tool for studying the spatial
behaviour of tourists and their impacts that has become increasingly integrated with GIS
environments (Cole, 2005; Lundgren
et al.
, 2006; Hunt
et al.
, 2010). Information provided
by simulations can allow planners to assess the effects of different management strategies.
Both probabilistic simulation and agent-based models (ABMs) are used in the development of
spatial simulation models (Gimblett and Skov-Peterson, 2008). Probabilistic models are
developed via the collection of data from tourists while undertaking their trips and/or from
data gained from observation (Sacchi
et al.
, 2001). This approach has been used, for example,
with respect to national park and wilderness camping and recreational behaviour (Lawson
and Manning, 2003; Lawson
et al.
, 2003, 2006). In contrast, ABMs are models of a collection
of autonomous decision-making entities (agents) in which each agent individually assesses its
situation and makes decisions on the basis of a set of rules that have been developed from 'real
world' data, and which are also used to calibrate and validate spatio-temporal simulation
models (O'Connor
et al.
, 2005). The repetitive competitive interactions between agents
within the system then provide information on behaviour at different points of time. As a
result of incorporating neural networks, evolutionary algorithms or other learning tech-
niques agents may be capable of evolving, thereby allowing unanticipated behaviours to
emerge (Bonabeau, 2002). The benefi ts of ABM over other modelling techniques are: (i)
ABM captures emergent phenomena; (ii) ABM provides a natural description of a system;
and (iii) ABM is fl exible. However, it is the ability of ABM to deal with emergent phenomena
which drives the other benefi ts (Bonabeau, 2002; Manning
et al.
, 2005). ABMs are particu-
larly useful for simulating tourism environments in which visitors are restricted to movement
on a network such as roads, trails or rivers and have therefore come to be used in a national
park and protected area context (Itami
et al.
, 2003; Cole, 2005). Hunt
et al.
(2010) also used
an ABM of recreational fi shing in northern Ontario, Canada, in order to demonstrate the
implications of different management scenarios with stakeholders.
The use of advanced tracking technologies
In the same way that the advent of the personal computer revolutionised use of GIS from a
user perspective, so further revolutions in informational and communication technology
provide new opportunities for spatial analysis. Paramount among the new developments is the
use of GPS devices and cellular phones, which both allow for the tracking of tourists in space-
time (Ahas
et al.
, 2007; Shoval and Isaacson, 2007a, 2010; Ahas
et al.
, 2008; Shoval, 2008; van
der Spek
et al.
, 2009; Chhreti
et al.
, 2010; Ahas, 2011). The method has a range of applica-
tions, including not only improved collection of data over traditional methods such as diaries,
but also management, planning and marketing applications. For example, Shoval (2010)
highlighted the possibility of using aggregative data obtained from GPS receivers in order to
better understand the impact of visitors on destinations and provided examples from
PortAventura amusement park in Catalonia, Spain (see also Russo
et al.
, 2010) and the Mini
Israel theme park in Israel (two enclosed outdoor environments), the Old City of Akko in
