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This is the development and application of computationally intensive approaches in geographical analysis. The term was first coined by Openshaw and colleagues working at the University of Leeds in the mid-1990s to describe the inductive approach used in the family of geographical analysis machines (see Openshaw et al., 1988), but has since been used to describe a much wider range of perspectives from a range of disciplines. The approach has been stimulated by precipitous falls in the cost of computer hardware and the proliferation of georeferenced digital data sources, and the environment to geocomputation is provided by geographical information systems (GIS). A distinctive characteristic of geocomputation is the creative and experimental use of GIS that it entails. It presents a broad but research-led approach to problem solving which emphasizes process over form, dynamics over statics, and interaction over passive response. Geocomputation is being used to devise improved, often application-specific, models of spatial distributions, enhanced visualizations of spatial phenomena and improved specification of spatial process. The spirit of geocomputation is fundamentally about matching technology with environment, process with data model, geometry and configuration with application, analysis with local context, and philosophy of science with practice.
There are some similarities between this approach and quantitative geography (see quantitative methods) and spatial analysis: indeed some of the same spatial problems (e.g. the modifiable areal unit problem, nonlinear optimization) have been revisited using a geocomputational perspective in order to overcome previous restrictive assumptions and to seek better quality results. Geocomputation is also providing the opportunity to apply new and novel computational tools to problems that previously could not be solved or have more recently become of interest. For some, the development of a grab-bag of techniques and applications under the umbrella term geocomputation is just a manifestation of a secular increase in our dependency upon computers, and is unlikely to exert any unifying effect upon science (see Couclelis, 1998). Yet for others it is much more than just using \'computers in geography\': it is at the same time a tool, a scientific paradigm and a whole new integrated way of thinking about spatial data collection, exploration, transformation, visualization and analysis. (PAL)
References Couclelis, H. 1998: Geocomputation in context. In P.A. Longley, S.M. Brooks, R. McDonnell and W. Macmillan, eds, Geocomputation: a primer. Chichester: John Wiley & Sons, 17-29. Openshaw, S., Charlton, M., Wymer, C. and Craft, A.W. 1988: A Mark I geographical analysis machine for the automated analysis of point data sets. International Journal of Geographical Information Systems 1: 335-58;
Suggested Reading Couclelis (1998). Longley, P.A. 1998: Foundations. In P.A. Longley, S.M. Brooks, R. McDonnell and W. Macmillan, eds, Geocomputation: a primer. Chichester: John Wiley & Sons, 3-15. Openshaw, S. and Alvanides, S. 1999: Applying GeoComputation to the analysis of spatial distributions. In P.A. Longley, M.F. Goodchild, D.J. Maguire and D.W. Rhind, eds, Geographical information systems: principles, techniques, management and applications. New York: John Wiley, 267-82. |
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