Please use this identifier to cite or link to this item:
Title: Reconstructing population density surfaces from areal data: A comparison of Tobler’s pycnophylactic interpolation method and area-to-point Kriging
Authors: Yoo, Eun-Hye
Kyriakidis, Phaedon
Tobler, Waldo
Keywords: Tobler’s Pycnophylactic Interpolation Method;Area-to-Point Kriging;Geostatistical approach;Compare
Category: Environmental Engineering
Field: Engineering and Technology
Issue Date: Jan-2010
Publisher: John Wiley & Sons
Source: Geographical Analysis, 2010, Volume 42, Issue 1, pages 78–98
Abstract: e 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.
ISSN: 0016-7363
1538-4632 (online)
DOI: 10.1111/j.1538-4632.2009.00783.x
Rights: The Ohio State University
Type: Article
Appears in Collections:Άρθρα/Articles

Show full item record

Citations 10

checked on Jun 11, 2019


Last Week
Last month
checked on Jun 17, 2019

Page view(s)

Last Week
Last month
checked on Jun 11, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.