| Sumario: | A methodology is developed for creating a surface-based representation of population that mitigates the analytical and cartographic problems due to the arbitrary nature of areal unit partitioning. The relationship between categorical ancillary data and population distribution is evaluated using dasymetric mapping, areal weighting, and empirical sampling techniques. The methodology is demonstrated by generating a 100-meter-resolution population surface from U.S. Census block group data for the southeast Pennsylvania region, with remote-sensing-derived land-cover data serving as ancillary data in the dasymetric mapping.
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