Geographic Information Systems, Spatial Modelling and Policy by Manfred M. Fischer, Peter Nijkamp

By Manfred M. Fischer, Peter Nijkamp

Geographical details platforms (GIS) offer an more suitable atmosphere for spatial info processing. the power of geographic details structures to deal with and examine spatially referenced information could be visible as a massive attribute which distinguishes GIS from info platforms built to serve the desires of commercial facts processing in addition to from CAD platforms or different structures whose fundamental target is map construction. This booklet, which includes contributions from a wide-ranging crew of overseas students, demonstrates the development which has been completed to this point on the interface of GIS know-how and spatial research and making plans. a few of the contributions compile theoretical and conceptual, technical and utilized concerns. issues lined comprise the layout and use of GIS and spatial types, AI instruments for spatial modelling in GIS, spatial statistical research and GIS, GIS and dynamic modelling, GIS in city making plans and coverage making, info structures for coverage overview, and spatial choice help platforms.

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Extra info for Geographic Information Systems, Spatial Modelling and Policy Evaluation

Sample text

Fully integrate all spatial analysis within the GIS software; 2. construct modules of spatial analysis that efficiently link with the GIS and effectively exploit the "spatial" information in the database; 3. leave the GIS and spatial analysis as two separate entities and simply import and export data in a common format between the two. The third approach is really a non-solution, since it ignores the distinctive characteristics of a spatial data base for use in spatial data analysis. Nevertheless, it seems to be the approach most taken in practice, due to the problems with proprietary data formats in commercial GIS and the limited facilities of often awkward macro languages (for an extensive discussion, see Kehris 1990a; Bivand 1990).

They would be: (1) demonstrations of the potential of the 32 S. Openshaw new technologies using padagogic and other illustrative data examples; (2) empirical evidence that the new methods out perform traditional alternatives when run on historic data for which there are existing results so that comparisons can be made; (3) illustrations that the new methods work in the data rich environments being created by GIS where there are no benchmarks based on traditional methods; and (4) the incorporation of AI procedures, perhaps hidden away, in general purpose analysis and modelling tools.

There certainly seems to be an opportunity to solve some of the outstanding hard problems by throwing computer power at them, in a manner that has previously characterised areas of physics, chemistry, and biology. It is argued, therefore, that it is quite possible that the modelling and analysis activities in GIS related fields will become dependent on AI technologies. It has been assumed previously that computers cannot be creative, yet seemingly AI methods will increasingly be able to assist the human user to generate new knowledge and concepts from data, insights that may well be unobtainable by any other route.

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