Evaluation of the positional difference between two common geocoding methods.

Geocoding, the process of matching addresses to geographic coordinates, is a necessary first step when using geographical information systems (GIS) technology. However, different geocoding methodologies can result in different geographic coordinates. The objective of this study was to compare the positional (i.e. longitude/latitude) difference between two common geocoding methods, i.e. ArcGIS (Environmental System Research Institute, Redlands, CA, USA) and Batchgeo (freely available online at http://www.batchgeo.com). Address data came from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5-11 years and their families participating in YMCA-administered, after-school programmes located in four geographically diverse metropolitan areas in the USA. Our analyses include baseline addresses (n = 748) collected from the parents of the children in the after school sites. Addresses were first geocoded to the street level and assigned longitude and latitude coordinates with ArcGIS, version 9.3, then the same addresses were geocoded with Batchgeo. For this analysis, the ArcGIS minimum match score was 80. The resulting geocodes were projected into state plane coordinates, and the difference in longitude and latitude coordinates were calculated in meters between the two methods for all data points in each of the four metropolitan areas. We also quantified the descriptions of the geocoding accuracy provided by Batchgeo with the match scores from ArcGIS. We found a 94% match rate (n = 705), 2% (n = 18) were tied and 3% (n = 25) were unmatched using ArcGIS. Forty-eight addresses (6.4%) were not matched in ArcGIS with a match score ≥80 (therefore only 700 addresses were included in our positional difference analysis). Six hundred thirteen (87.6%) of these addresses had a match score of 100. Batchgeo yielded a 100% match rate for the addresses that ArcGIS geocoded. The median for longitude and latitude coordinates for all the data was just over 25 m. Overall, the range for longitude was 0.04-12,911.8 m, and the range for latitude was 0.02-37,766.6 m. Comparisons show minimal differences in the median and minimum values, while there were slightly larger differences in the maximum values. The majority (>75%) of the geographic differences were within 50 m of each other; mostly <25 m from each other (about 49%). Only about 4% overall were ≥400 m apart. We also found geographic differences in the proportion of addresses that fell within certain meter ranges. The match-score range associated with the Batchgeo accuracy level "approximate" (least accurate) was 84-100 (mean = 92), while the "rooftop" Batchgeo accuracy level (most accurate) delivered a mean of 98.9 but the range was the same. Although future research should compare the positional difference of Batchgeo to criterion measures of longitude/latitude (e.g. with global positioning system measurement), this study suggests that Batchgeo is a good, free-of-charge option to geocode addresses.

[1]  William J. Drummond,et al.  Address Matching: GIS Technology for Mapping Human Activity Patterns , 1995 .

[2]  Gerard Rushton,et al.  Geocoding accuracy and the recovery of relationships between environmental exposures and health , 2008, International journal of health geographics.

[3]  Amy Trentham-Dietz,et al.  Geocoding Addresses from a Large Population-based Study: Lessons Learned , 2003, Epidemiology.

[4]  Dale L. Zimmerman,et al.  Estimating Spatial Intensity and Variation in Risk from Locations Subject to Geocoding Errors , 2006 .

[5]  T. Carpenter,et al.  Spatial analytical methods and geographic information systems: use in health research and epidemiology. , 1999, Epidemiologic reviews.

[6]  P. Rogerson,et al.  The Sage handbook of spatial analysis , 2009 .

[7]  J. Wakefield,et al.  Spatial epidemiology: methods and applications. , 2000 .

[8]  Duanping Liao,et al.  Accuracy and repeatability of commercial geocoding. , 2004, American journal of epidemiology.

[9]  Kypros Kypri,et al.  Potential biases due to geocoding error in spatial analyses of official data. , 2009, Health & place.

[10]  Richard L. Smith,et al.  Accuracy of commercial geocoding: assessment and implications , 2006, Epidemiologic perspectives & innovations : EP+I.

[11]  Gary Higgs,et al.  Positional accuracy and geographic bias of four methods of geocoding in epidemiologic research. , 2007, Annals of epidemiology.

[12]  Gerard Rushton,et al.  Geocoding in cancer research: a review. , 2006, American journal of preventive medicine.

[13]  S. Galea Macrosocial Determinants of Population Health , 2010 .

[14]  S. Galea,et al.  What Level Macro? Choosing Appropriate Levels to Assess How Place Influences Population Health , 2007 .

[15]  C. Coulton,et al.  Mapping Residents' Perceptions of Neighborhood Boundaries: A Methodological Note , 2001, American journal of community psychology.

[16]  Joanne S Colt,et al.  Positional Accuracy of Two Methods of Geocoding , 2005, Epidemiology.

[17]  Thomas O Talbot,et al.  Positional error in automated geocoding of residential addresses , 2003, International journal of health geographics.

[18]  J W Hogan,et al.  On the wrong side of the tracts? Evaluating the accuracy of geocoding in public health research. , 2001, American journal of public health.

[19]  S V Subramanian,et al.  Zip code caveat: bias due to spatiotemporal mismatches between zip codes and US census-defined geographic areas--the Public Health Disparities Geocoding Project. , 2002, American journal of public health.

[20]  David O'Sullivan,et al.  Beyond the Census Tract: Patterns and Determinants of Racial Segregation at Multiple Geographic Scales , 2008, American sociological review.

[21]  P. Reynolds,et al.  Post Office Box Addresses: A Challenge for Geographic Information System-Based Studies , 2003, Epidemiology.

[22]  S. Scobie Spatial epidemiology: methods and applications , 2003 .

[23]  Craig A. Knoblock,et al.  An effective and efficient approach for manually improving geocoded data. , 2008, International journal of health geographics.

[24]  Peter H Langlois,et al.  Match rate and positional accuracy of two geocoding methods for epidemiologic research. , 2006, Annals of epidemiology.

[25]  Gerard Rushton,et al.  Public health, GIS, and spatial analytic tools. , 2003, Annual review of public health.

[26]  Jeremy C. Weiss,et al.  Comparing a single-stage geocoding method to a multi-stage geocoding method: how much and where do they disagree? , 2007, International Journal of Health Geographics.