Refining Population Surface Models: Experiments with Northern Ireland Census Data

This paper compares and contrasts alternative methods for the construction of discontinuous population surface models based on the census and remotely sensed data from Northern Ireland. Two main methods of population distribution are employed: (1) a method based on redistribution from enumeration district (ED) and postcode centroids, and (2) a method based on dasymetric redistribution of ED population counts to suitable land cover zones from classified remotely sensed imagery. Refinements have been made to the centroid redistribution algorithm to accommodate an empirical measure of dispersion, and to allow redistribution in an anisotropic form. These refinements are evaluated against each other and the dasymetric method. The results suggest that all of the methods perform best in urban areas, and that while the refinements may improve the statistical performance of the models, this is at the expense of reduced spatial detail. In general, the techniques are highly sensitive to the spatial and population resolution of the input data.

[1]  I. Bracken,et al.  The Generation of Spatial Population Distributions from Census Centroid Data , 1989, Environment & planning A.

[2]  Atsuyuki Okabe,et al.  Variation in Count Data Transferred from a Set of Irregular Zones to a Set of Regular Zones Through the Point-in-Polygon Method , 1997, Int. J. Geogr. Inf. Sci..

[3]  D. Martin,et al.  Mapping population data from zone centroid locations. , 1989, Transactions.

[4]  Michael F. Goodchild,et al.  A Framework for the Areal Interpolation of Socioeconomic Data , 1993 .

[5]  Jennifer M. Robinson,et al.  Restoring Continuity: Exploration of Techniques for Reconstructing the Spatial Distribution Underlying Polygonized Data , 1997, Int. J. Geogr. Inf. Sci..

[6]  V. Mesev The use of census data in urban image classification , 1998 .

[7]  Ian J. Bateman,et al.  Improving Benefit Transfer Demand Functions: A GIS Approach , 1997 .

[8]  Robin Flowerdew,et al.  Data integration: Statistical methods for transferring data between zonal systems , 1991 .

[9]  M. Langford,et al.  Generating and mapping population density surfaces within a geographical information system. , 1994, The Cartographic journal.

[10]  John K. Wright A Method of Mapping Densities of Population: With Cape Cod as an Example , 1936 .

[11]  W. Tobler Smooth pycnophylactic interpolation for geographical regions. , 1979, Journal of the American Statistical Association.

[12]  I Bracken,et al.  Linkage of the 1981 and 1991 UK Censuses Using Surface Modelling Concepts , 1995, Environment & planning A.

[13]  Jonathan Raper,et al.  Postcodes: the new geography , 1992 .

[14]  Waldo Tobler,et al.  Linear pycnophylactic reallocation comment on a paper by D. Martin , 1999, Int. J. Geogr. Inf. Sci..

[15]  Trevor C. Bailey,et al.  Interactive Spatial Data Analysis , 1995 .

[16]  Peter F. Fisher,et al.  Modelling the Errors in Areal Interpolation between Zonal Systems by Monte Carlo Simulation , 1995 .

[17]  Peter F. Fisher,et al.  Modeling Sensitivity to Accuracy in Classified Imagery: A Study of Areal Interpolation by Dasymetric Mapping* , 1996 .

[18]  Danny Dorling,et al.  Map design for census mapping , 1993 .

[19]  Andrew A. Lovett,et al.  Assessing Hazardous Waste Transport Risks Using a GIS , 1996, Int. J. Geogr. Inf. Sci..

[20]  David J. Martin An Assessment of Surface and Zonal Models of population , 1996, Int. J. Geogr. Inf. Sci..