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Geodemographic Segmentation

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Encyclopedia of GIS

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Figure 1a and b
figure 1

Aggregation of spatially exhaustive subunit polygons into spatially exhaustive segments

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  1. Tryon, R.C.: Cluster analysis; correlation profile and orthometric (factor) analysis for the isolation of unities in mind and personality., Ann Arbor, Mich.: Edwards brother, inc., lithoprinters and publishers. viii, 122 p (1939)

    Google Scholar 

  2. Sokal, R.R., Sneath, P.H.A.: Principles of numerical taxonomy. Freeman W.H., San Francisco, xvi, 359 p (1963)

    Google Scholar 

  3. Park, R.E., et al.: The City. The University of Chicago Press, Chicago, Ill 239 p (1925)

    Google Scholar 

  4. Weiss, M.J.: The clustering of America, 1st edn. Harper & Row, New York, xvi, 416 p (1988)

    Google Scholar 

  5. Weiss, M.J.: Latitudes & attitudes: an atlas of American tastes, trends, politics, and passions: from Abilene, Texas to Zanesville, Ohio. 1st edn. Little, Brown, Boston, 224 p (1994)

    Google Scholar 

  6. Weiss, M.J.: The clustered world: how we live, what we buy, and what it all means about who we are. 1st edn. Little, Brown, Boston, viii, 323 p (2000)

    Google Scholar 

  7. Debenham, J., Clarke, G., Stillwell, J.: Extending geodemographic classification: a new regional prototype. Environ. Plann. A 35(6), 1025–1050 (2003)

    Article  Google Scholar 

  8. Hartigan, J.A.: Clustering algorithms, Wiley, New York, xiii, 351 p (1975)

    Google Scholar 

  9. Kaufman, L., Rousseeuw, P.J.: Finding groups in data: an introduction to cluster analysis. Wiley series in probability and mathematical statistics. Applied probability and statistics.: Wiley, New York, xiv, 342 p (1990)

    Google Scholar 

  10. Schèurmann, J.: Pattern classification: a unified view of statistical and neural approaches. Wiley, New York, xvii, 373 p (1996)

    Google Scholar 

  11. Balakrishnan, P., et al.: Comparative performance of the FSCL neural net and K-means algorithm for market segmentation. Eur. J. Oper. Res. 93(2), 346–357 (1996)

    Article  MATH  Google Scholar 

  12. Kumar, V., Karande, K.: The effect of retail store environment on retailer performance. J. Bus. Res. 49(2), 167–181 (2000)

    Article  Google Scholar 

  13. Palm, R.: Spatial Segmentation of the Urban Housing Market. Econom. Geogr. 54(3), 210–21 (1978)

    Article  Google Scholar 

  14. Brasington, D., Hite, D.: Demand for environmental quality: a spatial hedonic analysis. Reg. Sci. Urban Econ. 35(1), 57–82 (2005)

    Article  Google Scholar 

  15. Zabel, J.E.a.K.A.K.: Demand for air quality. Sage Urban Stud. Abstr. 29(1), 3–135 (2001)

    Google Scholar 

  16. Lipscomb, C., Farmer, M.: Household diversity and market segmentation within a single neighborhood. Ann. Reg. Sci. 39(4), 791–810 (2005)

    Article  Google Scholar 

  17. Bourassa, S., Hoesli, M., Peng, V.: Do housing submarkets really matter? J. Housing Econ. 12(1), 12–28 (2003)

    Article  Google Scholar 

  18. Fotheringham, A.S., Brunsdon, C., Charlton, M.: Geographically weighted regression: the analysis of spatially varying relationships. Wiley, Chichester, England; Hoboken, NJ, USA xii, 269 p (2002)

    Google Scholar 

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© 2008 Springer-Verlag

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Troy, A. (2008). Geodemographic Segmentation. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35973-1_456

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