Formalizing Place in Geographic Information Systems

  • Michael F. GoodchildEmail author
Part of the Social Disparities in Health and Health Care book series (SDHHC, volume 1)


The past four decades have witnessed a rapid and accelerating growth in the use of computers to handle geographic information. As machines, computers require that inputs be formalized, following well-defined rules and using shared definitions of terms. This requirement has created a fundamental tension with the informal world of human discourse, and nowhere is this more apparent than over the vague concept of place. The chapter explores this tension from various perspectives: current methods of geographic representation in digital form, inherent ambiguities, the case of the gazetteer, the role of volunteered geographic information, and place as an expression of context. Examples are used to illustrate the basic principles.


Geographic Information System Geographic Information Source Zone Volunteer Geographic Information Spatial Concept 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I thank Donald Janelle and Karl Grossner for their work in building the site with its ontology of spatial concepts.


  1. Burrough, P.A. and A.U. Frank, editors, 1996. Geographic Objects with Indeterminate Boundaries. London: Taylor and Francis.Google Scholar
  2. Duckham, M., 2009. Keynote paper: representation of the natural environment. In N. Mount, G. Harvey, P. Aplin, and G. Priestnall, editors, Representing, Modeling, and Visualizing the Natural Environment, pp. 11–20. Boca Raton: CRC Press.Google Scholar
  3. Eliot, J., 1987. Models of Psychological Space: Psychometric, Developmental and Experimental Approaches. New York: Springer-Verlag.Google Scholar
  4. Foresman, T.W., editor, 1998. The History of Geographic Information Systems: Perspectives from the Pioneers. Upper Saddle River, NJ: Prentice Hall.Google Scholar
  5. Fernández-Armesto, F., 2007. Amerigo: The Man Who Gave His Name to America. New York: Random House.Google Scholar
  6. Gardner, H., 1999. Intelligence Reframed: Multiple Intelligences for the 21st Century. New York: Basic Books.Google Scholar
  7. Goodchild, M.F., L. Anselin, and U. Deichmann, 1993. A framework for the areal interpolation of socioeconomic data. Environment and Planning A 25: 383–397.CrossRefGoogle Scholar
  8. Goodchild, M.F., M.J. Egenhofer, R. Fegeas, and C.A. Kottman, editors, 1999. Interoperating Geographic Information Systems. Boston: Kluwer Academic Publishers.Google Scholar
  9. Goodchild, M.F. and L.L. Hill, 2008. Introduction to digital gazetteer research. International Journal of Geographical Information Science 22(10): 1039–1044.CrossRefGoogle Scholar
  10. Goodchild, M.F. and N. Lam, 1980. Areal interpolation: a variant of the traditional spatial ­problem. Geoprocessing 1: 297–312.Google Scholar
  11. Hastings, J.T., 2008. Automated conflation of digital gazetteer data. International Journal of Geographical Information Science 22(10): 1109–1127.CrossRefGoogle Scholar
  12. Jones, C.B., R.S. Purves, P.D. Clough, and H. Joho, 2008. Modelling vague places with knowledge from the Web. International Journal of Geographical Information Science 22(10): 1045–1065.CrossRefGoogle Scholar
  13. Lopez, R.P., 2007. Neighborhood risk factors for obesity. Obesity 15: 2111–2119.CrossRefGoogle Scholar
  14. Maling, D.H., 1989. Measurement from Maps: Principles and Methods of Cartometry. New York: Pergamon.Google Scholar
  15. Montello, D.R., M.F. Goodchild, J. Gottsegen, and P. Fohl, 2003. Where’s downtown? Behavioral methods for determining referents of vague spatial queries. Spatial Cognition and Computation 3(2,3): 185–204.Google Scholar
  16. National Research Council (NRC), 2006. Learning to Think Spatially: GIS as a Support System in the K-12 Curriculum. Washington, DC: National Academies Press.Google Scholar
  17. Pickles, J., editor, 1995. Ground Truth: The Social Implications of Geographic Information Systems. New York: Guilford.Google Scholar
  18. Silverman, B.W., 1986. Density Estimation for Statistics and Data Analysis. London: Chapman and Hall.Google Scholar
  19. Sui, D.Z. and M.F. Goodchild, 2001. Guest editorial: GIS as media? International Journal of Geographical Information Science 15(5): 387–389.CrossRefGoogle Scholar
  20. Tobler, W.R., 1979. Smooth pycnophylactic interpolation for geographical regions. Journal of the American Statistical Association 74(367): 519–536.CrossRefGoogle Scholar
  21. Zhang, J.-X. and M.F. Goodchild, 2002. Uncertainty in Geographical Information. New York: Taylor and Francis.CrossRefGoogle Scholar
  22. Zook, M. and M. Graham, 2009. Mapping the GeoWeb: The spatial contours of Web 2.0 ­cyberspace. Paper presented at the Annual Meetings of the Association of American Geographers, Las Vegas.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of GeographyUniversity of CaliforniaSanta BarbaraCAUSA

Personalised recommendations