The United States Census Bureau conducts a count and representative sample of the American population at the beginning of each decade. Census data are important for congressional redistricting, distribution of governmental funds and planning purposes. Unfortunately, these extremely robust decadal surveys are still rife with limitations. For example, aggregated census population data have several analytical and cartographic problems because the partitioning of areal units is not always based on natural geographical features. Conventional dasymetric mapping techniques attempt to mitigate this effect by employing an areal interpolation technique that disaggregates spatial data using ancillary information (i.e., land use or land cover data).Previous research has demonstrated the utility of dasymetric techniques; however, many improvements remain possible. This research identified the major errors involved in conventional dasymetric mapping and examined the methods to extend conventional dasymetric mapping techniques by using alternative sources of ancillary data, including municipal zoning data and building-level population data. The alternative ancillary data helped to refine population estimates. Each technique was validated using the pycnophylactic property and it was found that the building level dasymetric method based on census data had preserved the population most accurately and with RMSE of zero. In addition, this research discussed about future development of dasymetric mapping.
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