Geographic Information Systems and Spatial Analysis in the Social Sciences
- Title
- Geographic Information Systems and Spatial Analysis in the Social Sciences
- Creator(s)
- Goodchild, Michael F.
- Editor(s)
- Aldenderfer, Mark
- Maschner, Herbert D. G.
- Date
- 1996
- Is Part Of
- Anthropology, Space, and Geographic Information Systems
- Pages
- 241 - 250
- Language
- eng
- Publisher
- Oxford University Press
- Place Published
- Oxford
- ISBN
- 978-0-19-508575-4
- Abstract
- Although geographers have used them for centuries, the idea that they might be part of the formal or informal process of data analysis and scientific inference is still novel in many areas of the social sciences. In economics, for example, the dominant paradigm emphasizes search for theories and principles that apply uniformly within human society or its economies, and if geographic areas such as nation-states are used as units of analysis, their role is more or less that of statistical samples, each equally representative of a hypothetical population of all possible nation-states. Within this paradigm (and I do not wish to suggest that it is the only paradigm within economics or that it is necessarily inappropriate), a list of nation-states, ordered alphabetically, is more precise and useful for analysis than a map, since maps tend to lump data values into coarse classes of color or shade and make it difficult to identify the attributes of small nation-states like Luxembourg or St. Lucia. Tables, on the other hand, present each nation state’s value clearly and precisely. The chapters in this book represent a striking departure from this orthodoxy, since each describes research that depends in some way on a belief in the importance of spatial context or in looking at data from a spatial perspective. This might mean merely looking at a map, despite the disadvantages already noted. Or it might mean direct reference to such primitive spatial concepts as adjacency, proximity, direction, or coincidence in space. We might choose to call this examination of data in spatial context GIS or spatial analysis, and the methods used might be mathematically sophisticated, computationally intensive, or simply intuitive—the chapters in this book cover a wide range of options. Taken together, however, it is clear that they represent a striking departure from the aspatial ways of thinking described earlier. It seems appropriate in this concluding chapter to attempt a summary of the main features and assumptions of spatial analysis and its limitations and impediments. One of the aims of GIS is to make spatial analysis easier, more flexible, and more powerful.
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