Improving Small-Area Population Estimation: An Integrated Geographic and Demographic Approach

Accurate and timely population information is essential for public planning and commercial applications. Traditional population estimates, however, are only available at aggregated geographic levels (e.g., state, county, etc.). To address this problem, a new bottom-up method was proposed for population estimation at the census block level by integrating high-resolution remotely sensed imagery and geographic information system (GIS) data and a demographic housing unit (HU) model. Two major components of the HU model, HU numbers and persons per household (PPH), were estimated by employing detailed information extracted from high-resolution remotely sensed imagery and GIS data. Further, population counts for each census block were generated through applying the HU model. Analysis of results suggests that the proposed integrated method performs reasonably well, as indicated by relatively small estimation errors. For a better assessment, the estimation accuracies of HU numbers, PPH, and population counts were compared with other widely applied techniques, and results indicated that this method significantly improved the accuracy. Finally, sensitivity analyses were conducted to evaluate the sources of errors for population estimates. Results indicate that, when compared to PPH estimates, the error associated with HU number estimates is a major source of small-area population estimation errors.