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Abstract Aggregated demographic datasets are associated with analytical and cartographic problems due to the arbitrary nature of areal unit partitioning. This article describes a methodology for generating a surface-based representation of population that mitigates these problems. This methodology uses dasymetric mapping and incorporates areal weighting and empirical sampling techniques to assess the relationship between categorical ancillary data and population distribution. As a demonstration, a 100-meter-resolution population surface is generated from U.S. Census block group data for the southeast Pennsylvania region. Remote-sensing-derived urban land-cover data serve as ancillary data in the dasymetric mapping.
Jeremy Mennis (Sat,) studied this question.