The analysis of geographically referenced sociodemographic data often requires the use of data collected at different spatial scales and/or different temporal resolutions. In addition, population data that are collected at one spatial resolution may be unsuitable for a particular research project, and these data must be redistributed to different spatial units of analysis. Researchers must overcome these challenges by employing a variety of areal interpolation techniques to make the data spatially compatible. Dasymetric mapping techniques have been demonstrated to be one means through which this can be achieved successfully. We provide an overview of areal interpolation techniques with an emphasis on dasymetric mapping. We illustrate an example in which population estimates and sociodemographic data are derived for different spatial units by employing dasymetric mapping methods that rely upon ancillary data from a variety of sources, including remotely sensed satellite imagery.