Influence of street reference data on geocoding quality

Abstract

Repeatability of street geocoding was characterized in terms of completeness and positional accuracy by using different street network datasets to geocode the same address input file. Match rates were highest for local street centrelines followed by StreetMap USA 2005 and TIGER 2000 data. Positional accuracy was highest for local street centrelines, while StreetMap USA 2005 and TIGER 2000 were nearly identical. Rural addresses were geocoded less accurately than urban addresses. Multi-family residential and commercial, institutional or industrial addresses were geocoded less accurately than urban single family residential addresses. The enhancement of TIGER 2000 data by commercial firms resulted in higher match rates but not in improved positional accuracy. The study has also highlighted the unique nature of multi-family and nonresidential addresses in terms of the quality of their street geocoded locations. When such addresses are of specific interest alternatives to traditional street geocoding may need to be considered.

Error propagation models to examine the effects of geocoding quality on spatial analysis of individual-level datasets

“…The positional accuracy for local street centerlines is known to be much better compared to TIGER 2000 data (e.g. Zandbergen, 2011) which directly translates into lower errors in the aggregation. Second, the errors are inversely proportional to the size of the polygons.…”

Turkish street addressing system and geocoding challenges

“…The street address is more useful than other descriptive numbers such as a personal identification number (PIN), serial number, or telephone number. However, because spatial data is extremely important for data processes and in international descriptions, the street address is very significant in terms of establishing national and international information infrastructures and determining geographical location features (Boqiu et al, 2010;Coetzee and Bishop, 2009;Coetzee and Cooper, 2007;Coetzee et al, 2008;Geymen et al, 2008;Henry and Boscoe, 2008;Lind, 2008;Zandbergen, 2008;Zandbergen, 2010).…”

Influence of Demographic and Health Survey Point Displacements on Distance-Based Analyses

“…In this locational inaccuracy setting, much of the previous literature has explored properties of the introduced error (Bonner et al, 2003; Cayo and Talbot, 2003; Ward et al, 2005; Rushton et al, 2006; Whitsel et al, 2006; Zhan et al, 2006; Goldberg et al, 2007; Kravets and Hadden, 2007; Zandbergen, 2007, 2008, 2011; Zimmerman et al, 2007, 2010; Zandbergen and Hart, 2009; Zandbergen et al, 2011) as well as its impact on subsequent spatially-based analyses (Burra et al, 2002; DeLuca and Kanaroglou, 2008; Mazumdar et al, 2008; Jacquez and Rommel, 2009; Zimmerman et al, 2010; Zinszer et al, 2010), where the errors are unintentionally introduced due to incorrect geocoding. A number of other studies have investigated the locational error that is intentionally introduced (Armstrong et al, 1999; Leitner and Curtis, 2004, 2006; Kamel Boulos et al, 2006; Olson et al, 2006; Wieland et al, 2008), such as with DHS point displacement.…”