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Embedded GIS in environmental management

Kurt Fedra

Kurt Fedra
Environmental Software & Services
[email protected]

Environmental and resource management problems are both spatially distributed and determined by complex processes and relationships, involving numerous interacting elements with multiple attributes, and a dynamic behavior that goes well beyond the analytical capabilities of most commercial GIS software. The tools required for analysis include dynamic and spatially distributed simulation models, optimization models, expert systems, and decision support tools based on concepts of systems analysis and operations research rather than only geostatistics. The primary paradigm of a GIS is the map, an inherently static concept of limited attributes. While modern GIS extend the scope of what can be done within this paradigm towards digital cartography considerably, and elaborate applications can be built within existing GIS systems and powerful and flexible tool kits (see, for example, there is also a broad class of problem situations that do involve spatial elements, but where the GIS components are only auxiliary to another problem solving approach (Fedra 1994).

The main features of a spatial information system that go beyond classical GIS capabilities and may require an alternative approach of embedded GIS are:

  • dynamics including real-time aspects and control
  • complex behavior (simulation) and multiple attributes
  • decision support orientation, optimization

which are all somewhat related, so that any good application example for embedded GIS solutions may include any or all of the above features.

The obvious answer is to link and integrate GIS functionality with specialized tools for complex and dynamic analysis. The practical question is often how to couple the different tools smoothly, which approach and paradigm drives the overall application. Many GIS systems are open to link external components that read and generate georeferenced data, using the GIS, its data structures, user interface and display capabilities as the overall framework. Native analytical functions, however, are usually limited to Boolean overlay analysis, buffers (or more general, neighborhood analysis), network and routing tasks, and spatially distributed processes that can be expressed in terms of cellular automata, often applied in the context of urban development or forest fire studies (Clarke and Gaydos, 1998; Liu, 2002; Li and Yeh, 2002).

Fig 1 A complex georeferenced object: airport as emisison source and monitoring station