A fine-scale spatial population distribution on the High-resolution Gridded Population Surface and application in Alachua County, Florida

• We use the relationship between population density and parcel types for modeling.
• We improve the approach to mapping the High-Resolution Gridded Population Surface.
• We compare the accuracy of the HGPS and a Land Cover-based Population Product.
• We apply the HGPS to a case study to demonstrate its advantages.
• We compare the HGPS with LCPP to examine differences in spatial heterogeneity.

Geospatial techniques, using Geographic Information Systems and remote sensing data, have become more commonly used with dasymetric modeling of fine-scale demographic data. In this study, we apply a dasymetric approach using the Heuristic Sampling Method for 2010 parcel data to disaggregate population counts from the 2010 U.S. Census into a quadrilateral grid composed of 30 × 30 m cells covering the Alachua County, Florida. The final output, termed the High-resolution Gridded Population Surface (HGPS), is compared to a land cover-based population product (LCPP) and the detail of each product is assessed. Results suggest that the HGPS provides increased spatial heterogeneity and more detail in the boundaries of populated areas over the use of census blocks or land cover lots. For an example of the final output, we use a case study at the Cabot–Koppers Superfund Site to demonstrate the advantages of the HGPS over the LCPP. The HGPS is expected to serve as a more accurate input in various research fields, such as public health, crime analysis, and climate change. The approach outlined provides an improved means of producing spatially-explicit population grids where fine-scale ancillary data, such as parcel data, is available.