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Using Areal Interpolation Methods In Geographic Information Systems

Author

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  • Robin Flowerdew
  • Mick Green
  • Evangelos Kehris

Abstract

ABSTRACT This paper reports on a research project concerned with the areal interpolation problem—the problem of comparing different data sets when they have been made available for different zonal systems. Our approach is based on using additional information to guide the interpolation process. This paper emphasizes recent work applying the method to Poisson and binomially distributed data. There is also discussion of how the method can best be implemented in a geographic information system.

Suggested Citation

  • Robin Flowerdew & Mick Green & Evangelos Kehris, 1991. "Using Areal Interpolation Methods In Geographic Information Systems," Papers in Regional Science, Wiley Blackwell, vol. 70(3), pages 303-315, July.
    • Handle: RePEc:bla:presci:v:70:y:1991:i:3:p:303-315
    DOI: 10.1111/j.1435-5597.1991.tb01734.x
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    Cited by:

    1. Eckhardt Bode, 2011. "Annual educational attainment estimates for U.S. counties 1990–2005," Letters in Spatial and Resource Sciences, Springer, vol. 4(2), pages 117-127, July.
    2. A S Mugglin & B P Carlin & L Zhu & E Conlon, 1999. "Bayesian Areal Interpolation, Estimation, and Smoothing: An Inferential Approach for Geographic Information Systems," Environment and Planning A, , vol. 31(8), pages 1337-1352, August.
    3. Huyen DO VAN & Christine THOMAS-AGNAN & Anne VANHEMS, 2014. "Testing Areal Interpolation Methods With Us Census 2010 Data," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 40, pages 83-96.
    4. Morito Tsutsumi & Daisuke Murakami, 2014. "New Spatial Econometrics–Based Areal Interpolation Method," International Regional Science Review, , vol. 37(3), pages 273-297, July.
    5. Jonathan R. Bradley & Christopher K. Wikle & Scott H. Holan, 2016. "Bayesian Spatial Change of Support for Count-Valued Survey Data With Application to the American Community Survey," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 472-487, April.
    6. Daniel Baldwin Hess, 2007. "Transformation of Spatial Data to a New Zone System: A Survey of US Metropolitan Planning Organizations," Environment and Planning B, , vol. 34(3), pages 483-500, June.
    7. M F Goodchild & L Anselin & U Deichmann, 1993. "A Framework for the Areal Interpolation of Socioeconomic Data," Environment and Planning A, , vol. 25(3), pages 383-397, March.
    8. Benjamin Spaulding & Robert Cromley, 2007. "Integrating the maximum capture problem into a GIS framework," Journal of Geographical Systems, Springer, vol. 9(3), pages 267-288, September.
    9. P F Fisher & M Langford, 1995. "Modelling the Errors in Areal Interpolation between Zonal Systems by Monte Carlo Simulation," Environment and Planning A, , vol. 27(2), pages 211-224, February.

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