Skip to main content

Reconstructing Population Density Surfaces from Areal Data: A Comparison of Tobler's Pycnophylactic Interpolation Method and Area‐to‐Point Kriging. Tobler’s Pycnophylactic

Buy Article:

$43.00 plus tax (Refund Policy)

We compare Tobler's pycnophylactic interpolation method with the geostatistical approach of area‐to‐point kriging for distributing population data collected by areal unit in 18 census tracts in Ann Arbor for 1970 to reconstruct a population density surface. In both methods, (1) the areal data are reproduced when the predicted population density is upscaled; (2) physical boundary conditions are accounted for, if they exist; and (3) inequality constraints, such as the requirement of non‐negative point predictions, are satisfied. The results show that when a certain variogram model, that is, the de Wijsian model corresponding to the free‐space Green's function of Laplace's equation, is used in the geostatistical approach under the same boundary condition and constraints with Tobler's approach, the predicted population density surfaces are almost identical (up to numerical errors and discretization discrepancies). The implications of these findings are twofold: (1) multiple attribute surfaces can be constructed from areal data using the geostatistical approach, depending on the particular point variogram model adopted—that variogram model need not be the one associated with Tobler's solution and (2) it is the analyst's responsibility to justify whether the smoothness criterion employed in Tobler's approach is relevant to the particular application at hand. A notable advantage of the geostatistical approach over Tobler's is that it allows reporting the uncertainty or reliability of the interpolated values, with critical implications for uncertainty propagation in spatial analysis operations.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Language: English

Document Type: Research Article

Affiliations: 1: Department of Geography, University at Buffalo, The State University of New York, Buffalo, NY 2: Department of Geography, University of California, Santa Barbara, CA

Publication date: 2010-01-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more