Incorporating GIS Building Data and Census Housing Statistics for Sub-Block-Level Population Estimation

Abstract

This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating census block areas and calculating the respective housing statistics. We then applied the model to estimate populations for sub-artificial-block areas and assessed the estimates with census populations of the areas. Our analyses indicate that the average percent error of population estimation for sub-artificial-block areas is comparable to those for sub-census-block areas of the same size relative to associated blocks. The smaller the sub-block-level areas, the higher the population estimation errors. For example, the average percent error for residential areas is approximately 0.11 percent for 100 percent block areas and 35 percent for 5 percent block areas.

Department(s)

Geography, Geology, and Planning

Document Type

Article

DOI

https://doi.org/10.1080/00330120701724251

Keywords

block population, dasymetric mapping, population estimation, population interpolation, sub-block

Publication Date

2008

Journal Title

The Professional Geographer

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