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Articles: Methods, Models, and GIS

Representation and Spatial Analysis in Geographic Information Systems

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Pages 574-594
Published online: 29 Feb 2008
 

Abstract

A common—perhaps modal—representation of geography in spatial analysis and geographic information systems is native (unexamined) objects interacting based on simple distance and connectivity relationships within an empty Euclidean space. This is only one possibility among a large set of geographic representations that can support quantitative analysis. Through the vehicle of GIS, many researchers are adopting this representation without realizing its assumptions or its alternatives. Rather than locking researchers into a single representation, GIS could serve as a toolkit for estimating and exploring alternative geographic representations and their analytical possibilities. The article reviews geographic representations, their associated analytical possibilities and relevant computational tools in the combined spatial analysis and GIScience literatures. The discussion identifies several research and development frontiers, including analytical gaps in current GIS software.

Notes

1. “Analysis” is a multifaceted term. We refer here to its precise mathematical definition as the class of sciences that examines exact relations between quantities or magnitudes ( Webster's Unabridged Dictionary 1998 Webster's Unabridged Dictionary 1998. http://www.dictionary.com (last accessed 9 May 2003).  [Google Scholar]). Analysis can only examine real-world properties that are measurable, countable, or formally comparable. This definition is consistent with the spatial analytic tradition in modern geography (Taaffe 1974 Taaffe, E. J. 1974. The spatial view in context. Annals of the Association of American Geographers, 64: 116. [Taylor & Francis Online], [Web of Science ®] [Google Scholar]). While there are other valid forms of inquiry, including narratives and graphics, these are not the direct concern of the discussion in this article.

2. Following standard usage, we use the term “geographic information systems” (GIS) to refer to the technology and “geographic information science” (GIScience) to refer to the theories and methods that underlie the technological implementation.

3. We purposely avoid naming any commercial or public-license GIS software directly. When we use the phrase “most GIS software” (or a variation), we imply precisely that: there is one or a very small number of software packages to which this observation does not apply. We decline to name the specific GIS software, either in a positive or a negative light.

4. “Countable” means that we can derive a one-to-one correspondence between the set in question and the set of natural numbers. In 1873, Georg Cantor proved that different “sizes” of infinite sets exist, with the natural numbers being the smallest. The set of irrational numbers is a larger and uncountable infinite set (Borowski and Borwein 1991 Borowski, E. J. and Borwein, J. M. 1991. Dictionary of mathematics, New York: HarperCollins.  [Google Scholar]). The term “σ-bounded” is often used to designate “countably bounded.”

5. See Flake (2000) Flake, G. 2000. The computational beauty of nature, Cambridge, MA: MIT Press.  [Google Scholar] for an excellent discussion of the relationships between computability and natural (including human-made) systems.

6. More precisely, this set is the Borelσ-algebra associated with (X, d L ). This is the smallest σ-algebra that contains the open subsets defined by (X,dL ). The σ-algebra of a set is a collection of subsets that contains: (1) the set itself; (2) the empty set; (3) the complements of all members of the set; and (4) all countable unions of members of the set (Borowski and Borwein 1991; Borowski, E. J. and Borwein, J. M. 1991. Dictionary of mathematics, New York: HarperCollins.  [Google Scholar] see Beguin and Thisse 1979 Beguin, H. and Thisse, J. F. 1979. An axiomatic approach to geographical space. Geographical Analysis, 11: 32541. [Crossref] [Google Scholar] for an alternative definition). Any Borel set is measurable, meaning that we can define a “measure” as indicated in the main text (see Haaser and Sullivan 1971 Haaser, N. B. and Sullivan, J. A. 1971. Real analysis, New York: Dover.  [Google Scholar]).

7. Note that the concept of “area” does not require a metric space topology; see Casati, Smith, and Varzi (1998) Casati, R., Smith, B. and Varzi, A. C. 1998. “Ontological tools for geographic representation”. In Formal ontology in information systems, Edited by: Guarino, N. 7785. Amsterdam: IOS Press.  [Google Scholar].

8. O ( ) or “big oh” notation indicates the order or general complexity class of the algorithm in the worst case. For example, O(n 2) states that the algorithm will require no more than n 2 operations, subject to a proportionality constant. For more information on complexity analysis, see Garey and Johnston (1979) Garey, M. R. and Johnson, D. S. 1979. Computers and intractability: A guide to the theory of NP-completeness, New York: W. H. Freeman and Company.  [Google Scholar] and Sipser (1997) Sipser, M. 1997. Introduction to the theory of computation, Boston: PWS Publishing.  [Google Scholar].

9. The law of transportation refraction assumes a cost-density field with no points of concentration or other impenetrable objects that can “block” shortest paths. Incorporating these objects requires an analogous concept of diffusion. Thanks to Mike Goodchild for pointing this out.

10. Or, more precisely, cells. A cell is a connected two-dimensional region with no “holes.” See Worboys (1995) Worboys, M. F. 1995. GIS: A computing perspective, London: Taylor and Francis.  [Google Scholar] for a more precise definition.

11. A simple line is a one-dimensional spatial object that is topologically equivalent to a straight line (Worboys 1995 Worboys, M. F. 1995. GIS: A computing perspective, London: Taylor and Francis.  [Google Scholar]): in other words, the line does not “cross” itself.

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