Geoscience Reference
In-Depth Information
systems that are not DSS in the truest sense. Spatial decision support systems (SDSS) add an explic-
itly spatial component through the use of geo-referenced data and have evolved in parallel with DSS
since the 1970s (Densham and Goodchild 1989). In many ways, SDSS are like GIS but with a higher
level of analytical and statistical modelling capability (Ayeni 1998), while Birkin et al. (1996) use
the term
intelligent GIS
to refer to a generation of enhanced GIS with statistical, mathematical
and
what if
modelling capabilities that are essentially SDSS. There are a plethora of SDSS devel-
oped for a wide spectrum of spatially related applications such as for land-use planning (Matthews
et al. 1999), agriculture (MicroLEIS DSS) (De la Rosa et al. 2004), environmental management
(GReenspace Assessment System [GRAS]) (Pelizaro et al. 2009), transportation (Tarantilis and
Kiranoudis 2002), sustainable development (Banai 2005), water resource management (WinBOS)
(Uran et al. 2003), aquaculture (Nath et al. 2000), forest protection (Vacik and Lexer 2001), solid
water planning (MacDonald 1996) and location planning (Daniel 1992), among others. Collections
of other applications are included in Birkin et al. (1996), Timmermans (1998), Kersten et al. (2000)
and Thomas and Humenik-Sappington (2009).
Planning support systems (PSS) are another type of DSS used in a range of planning contexts,
which date back to the 1950s (Klosterman 2001; Geertman and Stillwell 2002; Batty 2008), and
are designed to support planners in decision-making at various stages in the planning process. In
contrast to SDSS, PSS tend to focus on long-range problems and strategic issues and are often con-
structed specifically for group interaction and discussion with relevant stakeholders (Klosterman
1995; Geertman and Stillwell 2004), for example, public participation GIS and applications of web
GIS. Moreover, Sharifi et al. (2004) note that PSS are focussed on the second phase of the planning
and decision-making framework of Simon (1960), that is, the design phase, whereas SDSS are more
involved in the choice or evaluation phase.
ES differ from these DSSs (and their variants SDSS and PSS) in that they tend to be developed
to solve relatively focussed and narrowly defined problems, while DSSs refer to systems that are for
much more open-ended and interactive problem-solving. It is useful to think of DSS as providing a
problem-solving framework in which ES are embedded. DSSs are used when the solution involves
a mixture of different methods and numerous decision criteria, which are often user-defined; there
is support for individual or group decision-making; the system is user-friendly and flexible and
improves the effectiveness of decisions; the decision-maker has complete control of the process;
access is provided to a variety of data sources; it can be employed as a stand-alone tool; and the need
for support is on an
ad hoc
basis and not predetermined as with ES (Malczewski 1997; Rodriguez-
Bachiller and Glasson 2004; Turban et al. 2005).
Rodriguez-Bachiller and Glasson (2004) use a series of criteria to distinguish DSS from ES:
objectives, decision-maker, orientation, user and problem area. The objective of ES is to replicate
humans by taking the encapsulated knowledge and applying this to a problem, while the objec-
tive of DSS is much broader, that is, to help humans in problem-solving and decision-making.
The decision-maker in the case of an ES is the actual system, while in DSS, the user of the system
makes the decision based on the outcomes provided by the system. The user of an ES tends to be an
individual, while the stakeholders for a DSS are normally a wider group.
11.7 INTEGRATION OF GIS WITH ES
Spatial decision-making is a complex task and GIS has been the traditional tool for supporting
this process in various geographical domains such as resource and environmental management,
land infrastructure, urban and regional planning and transportation (Sharifi and Rodriguez 2002).
Although GIS has in-built information management
and spatial analysis capabilities, only a few GIS
such as IDRISI and ILWIS contain explicit planning and decision-making functions. Many authors
have criticised GIS for being too generic (Batty 2008), unable to incorporate decision-makers' pref-
erences and evaluate alternative solutions with conflicting criteria and objectives (Laaribi et al.
1996) or to adequately support systematic decision-making processes (Leung 1997; Sharifi and
