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Quantifying geocode location error using GIS methods

BACKGROUND: The Metropolitan Atlanta Congenital Defects Program (MACDP) collects maternal address information at the time of delivery for infants and fetuses with birth defects. These addresses have been geocoded by two independent agencies: (1) the Georgia Division of Public Health Office of Health...

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Autores principales: Strickland, Matthew J, Siffel, Csaba, Gardner, Bennett R, Berzen, Alissa K, Correa, Adolfo
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852798/
https://www.ncbi.nlm.nih.gov/pubmed/17408484
http://dx.doi.org/10.1186/1476-069X-6-10
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author Strickland, Matthew J
Siffel, Csaba
Gardner, Bennett R
Berzen, Alissa K
Correa, Adolfo
author_facet Strickland, Matthew J
Siffel, Csaba
Gardner, Bennett R
Berzen, Alissa K
Correa, Adolfo
author_sort Strickland, Matthew J
collection PubMed
description BACKGROUND: The Metropolitan Atlanta Congenital Defects Program (MACDP) collects maternal address information at the time of delivery for infants and fetuses with birth defects. These addresses have been geocoded by two independent agencies: (1) the Georgia Division of Public Health Office of Health Information and Policy (OHIP) and (2) a commercial vendor. Geographic information system (GIS) methods were used to quantify uncertainty in the two sets of geocodes using orthoimagery and tax parcel datasets. METHODS: We sampled 599 infants and fetuses with birth defects delivered during 1994–2002 with maternal residence in either Fulton or Gwinnett County. Tax parcel datasets were obtained from the tax assessor's offices of Fulton and Gwinnett County. High-resolution orthoimagery for these counties was acquired from the U.S. Geological Survey. For each of the 599 addresses we attempted to locate the tax parcel corresponding to the maternal address. If the tax parcel was identified the distance and the angle between the geocode and the residence were calculated. We used simulated data to characterize the impact of geocode location error. In each county 5,000 geocodes were generated and assigned their corresponding Census 2000 tract. Each geocode was then displaced at a random angle by a random distance drawn from the distribution of observed geocode location errors. The census tract of the displaced geocode was determined. We repeated this process 5,000 times and report the percentage of geocodes that resolved into incorrect census tracts. RESULTS: Median location error was less than 100 meters for both OHIP and commercial vendor geocodes; the distribution of angles appeared uniform. Median location error was approximately 35% larger in Gwinnett (a suburban county) relative to Fulton (a county with urban and suburban areas). Location error occasionally caused the simulated geocodes to be displaced into incorrect census tracts; the median percentage of geocodes resolving into incorrect census tracts ranged between 4.5% and 5.3%, depending upon the county and geocoding agency. CONCLUSION: Geocode location uncertainty can be estimated using tax parcel databases in a GIS. This approach is a viable alternative to global positioning system field validation of geocodes.
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spelling pubmed-18527982007-04-19 Quantifying geocode location error using GIS methods Strickland, Matthew J Siffel, Csaba Gardner, Bennett R Berzen, Alissa K Correa, Adolfo Environ Health Research BACKGROUND: The Metropolitan Atlanta Congenital Defects Program (MACDP) collects maternal address information at the time of delivery for infants and fetuses with birth defects. These addresses have been geocoded by two independent agencies: (1) the Georgia Division of Public Health Office of Health Information and Policy (OHIP) and (2) a commercial vendor. Geographic information system (GIS) methods were used to quantify uncertainty in the two sets of geocodes using orthoimagery and tax parcel datasets. METHODS: We sampled 599 infants and fetuses with birth defects delivered during 1994–2002 with maternal residence in either Fulton or Gwinnett County. Tax parcel datasets were obtained from the tax assessor's offices of Fulton and Gwinnett County. High-resolution orthoimagery for these counties was acquired from the U.S. Geological Survey. For each of the 599 addresses we attempted to locate the tax parcel corresponding to the maternal address. If the tax parcel was identified the distance and the angle between the geocode and the residence were calculated. We used simulated data to characterize the impact of geocode location error. In each county 5,000 geocodes were generated and assigned their corresponding Census 2000 tract. Each geocode was then displaced at a random angle by a random distance drawn from the distribution of observed geocode location errors. The census tract of the displaced geocode was determined. We repeated this process 5,000 times and report the percentage of geocodes that resolved into incorrect census tracts. RESULTS: Median location error was less than 100 meters for both OHIP and commercial vendor geocodes; the distribution of angles appeared uniform. Median location error was approximately 35% larger in Gwinnett (a suburban county) relative to Fulton (a county with urban and suburban areas). Location error occasionally caused the simulated geocodes to be displaced into incorrect census tracts; the median percentage of geocodes resolving into incorrect census tracts ranged between 4.5% and 5.3%, depending upon the county and geocoding agency. CONCLUSION: Geocode location uncertainty can be estimated using tax parcel databases in a GIS. This approach is a viable alternative to global positioning system field validation of geocodes. BioMed Central 2007-04-04 /pmc/articles/PMC1852798/ /pubmed/17408484 http://dx.doi.org/10.1186/1476-069X-6-10 Text en Copyright © 2007 Strickland et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Strickland, Matthew J
Siffel, Csaba
Gardner, Bennett R
Berzen, Alissa K
Correa, Adolfo
Quantifying geocode location error using GIS methods
title Quantifying geocode location error using GIS methods
title_full Quantifying geocode location error using GIS methods
title_fullStr Quantifying geocode location error using GIS methods
title_full_unstemmed Quantifying geocode location error using GIS methods
title_short Quantifying geocode location error using GIS methods
title_sort quantifying geocode location error using gis methods
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852798/
https://www.ncbi.nlm.nih.gov/pubmed/17408484
http://dx.doi.org/10.1186/1476-069X-6-10
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