Positional Accuracy and Geographic Bias of Four Methods of Geocoding in Epidemiologic Research

Mario Schootman, David A. Sterling, James Struthers, Yan Yan, Ted Laboube, Brett Emo, Gary Higgs

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Purpose: We examined the geographic bias of four methods of geocoding addresses using ArcGIS, commercial firm, SAS/GIS, and aerial photography. We compared "point-in-polygon" (ArcGIS, commercial firm, and aerial photography) and the "look-up table" method (SAS/GIS) to allocate addresses to census geography, particularly as it relates to census-based poverty rates. Methods: We randomly selected 299 addresses of children treated for asthma at an urban emergency department (1999-2001). The coordinates of the building address side door were obtained by constant offset based on ArcGIS and a commercial firm and true ground location based on aerial photography. Results: Coordinates were available for 261 addresses across all methods. For 24% to 30% of geocoded road/door coordinates the positional error was 51 meters or greater, which was similar across geocoding methods. The mean bearing was -26.8 degrees for the vector of coordinates based on aerial photography and ArcGIS and 8.5 degrees for the vector based on aerial photography and the commercial firm (p < 0.0001). ArcGIS and the commercial firm performed very well relative to SAS/GIS in terms of allocation to census geography. For 20%, the door location based on aerial photography was assigned to a different block group compared to SAS/GIS. The block group poverty rate varied at least two standard deviations for 6% to 7% of addresses. Conclusion: We found important differences in distance and bearing between geocoding relative to aerial photography. Allocation of locations based on aerial photography to census-based geographic areas could lead to substantial errors.

Original languageEnglish
Pages (from-to)464-470
Number of pages7
JournalAnnals of Epidemiology
Volume17
Issue number6
DOIs
StatePublished - Jun 2007

Keywords

  • Bias
  • GPS
  • Geocoding
  • Geography

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