Environmental Engineering Reference
In-Depth Information
Identifying the characteristic aspect that most likely describes the tendency of a
data series is one of the core challenges of data analysis. In contrast to time, space
enables for-and-back dynamics: an entity apparently might move aimlessly but is
heading in an overall direction. Plotting single observations (or a calculation from a
model) of the movement of an entity in a GIS-map (by joining them), makes
directions of spatial trends obvious and calculable.
Scenarios
Modelling dynamics, especially projecting known behaviour of an ecosystem to a
probable future, must deal with inaccuracies and uncertainties (see also Chap. 2 on
Model Development). Methodically immanent inaccuracies are in the end the result
of the complexity of the systems we observe: the more parameters a monitoring
involves, the more variables a model calculates, the bigger the methodical error is
likely to be. Calculating an area-wide parameter based on a limited number of
measurement points increases the propagated error, although each measurement
might be accurate. That especially applies for projections of the development of
highly dynamic components of ecosystems like meteorological events. Describing
scenarios is an appropriate method in dealing with these uncertainties and increases
the relevance of a projection. Descriptions can be used to estimate the spectrum of
possible future scenarios, and determine boundary conditions of the simulations
scenarios, which fix the edges of complex IEM. Comparing the results of calcula-
tions based on different scenarios gives a hint about the possible dynamics of an
ecological system.
22.4 Example Applications
Awide range of IEMexists worldwide. The spectrum of IEM, in a broad sense, spans
from global world models via regional landscape models up to sophisticated deci-
sion support systems. Classic examples for world models are the computer simula-
tions world3 - more system oriented than spatially explicit - used by the Club of
Rome (The Limits of Growth, Meadows et al. 1972) and the spectrum of models
used by the IPCC to describe and project the ongoing climate change (IPCC 2007).
With the increasing power available with GIS and the desire for integrated
approaches for management, many example applications have been developed that
address problems in atmosphere-surface systems, hydrology, forestry and biology
(see e.g. Basnyat et al. 2000; DeVantier et al. 1993; Goodchild 1993, 1996; Haan
1996; Su 1997). The development of IEM, now using the GIS capabilities to be more
spatially explicit, does not end with an increasing number of decision support
systems dealing with questions of resource management and environmental policy
support (Denzer 2005; Freda 1995; Keen 1978; Lam et al. 2004; Struss 2009).
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