High-resolution dasymetric population estimation using property tax records, census group quarters, and the US National Grid

Authors: Georgianna Strode*, Florida State University/FREAC, Victor Mesev, Florida State University
Topics: Population Geography
Keywords: census, population, dasymetric, cadastral, grid, USNG, Florida
Session Type: Paper
Day: 4/14/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Napoleon A3, Sheraton, 3rd Floor
Presentation File: No File Uploaded

Dasymetric population estimation techniques improve the resolution of population counts by combining ancillary data sources with census data. Property tax records are promising ancillary sources as these rich local databases contain information useful for prediction of residency. However, errors arise with group living situations such as nursing homes, prisons, and colleges as these features are not consistently recorded in local property records. A solution is to include group quarter census data to identify areas with high numbers of residents. The first part of this research introduces an expanded version of Maantay’s original dasymetric formula that more accurately reflects group living. The second part of this research aggregates population estimates to a gridded format using the U.S. National Grid (USNG). This grid system offers the standard benefits of any grid system: minimizing the impact of the Modifiable Areal Unit Problem, maintaining data density, avoidance of changing zonal boundaries, and improved modeling, statistics, and visualizations. However, the USNG goes a few steps further as it is a scalable, standardized grid system recognized by FEMA and national geospatial commissions for its ability to accurately locate any area on earth at multiple scales. This presentation covers the complete process of the expanded dasymetric formula to produce an estimate for individual land parcels through the gridding procedure to show population estimates at multiple scales. The study area is the U.S. state of Florida with its 9 million land parcels.

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