Positional Accuracy of TIGER 2000 and 2009 Road Networks

Abstract

The Topologically Integrated Geographic Encoding and Referencing (TIGER) data are an essential part of the US Census and represent a critical element in the nation's spatial data infrastructure. TIGER data for the year 2000, however, are of limited positional accuracy and were deemed of insufficient quality to support the 2010 Census. In response the US Census Bureau embarked on the MAF/TIGER Accuracy Improvement Project (MTAIP) in an effort to improve the positional accuracy of the database, modernize the data processing environment and improve cooperation with partner agencies. Improved TIGER data were released for the entire US just before the 2010 Census. The current study characterizes the positional accuracy of the TIGER 2009 data compared with the TIGER 2000 data based on selected road intersections. Three US counties were identified as study areas and in each county 100 urban and 100 rural sample locations were selected. Features in the TIGER 2000 and 2009 data were compared with reference locations derived from high resolution natural color orthoimagery. Results indicate that TIGER 2009 data are much improved in terms of positional accuracy compared with the TIGER 2000 data, by at least one order of magnitude across urban and rural areas in all three counties for most accuracy metrics. TIGER 2009 is consistently more accurate in urban areas compared with rural areas, by a factor of at least two for most accuracy metrics. Despite the substantial improvement in positional accuracy, large positional errors of greater than 10 m are relatively common in the TIGER 2009 data, in most cases representing remnant segments of minor roads from older versions of the TIGER data. As a result, based on the US Census Bureau's suggested accuracy metric, the TIGER 2009 data meet the accuracy expectation of 7.6 m for two of the three urban areas but for none of the three rural areas. The suggested metric is based on the National Standard for Spatial Data Accuracy (NSSDA) protocol and was found to be very sensitive to the presence of a small number of very large errors. This presents challenges during attempts to characterize the accuracy of TIGER data or other spatial data using this protocol.

Short‐Term Impacts of the Megaurbanizations of New Delhi and Los Angeles Between 2000 and 2009

“…It was initially created to facilitate and organize the 1990 Census (https://www.census.gov/newsroom/blogs/director/2014/11/happy-25th-anniversary-tiger.html). The 2010 TIGER/Line® road data used here have an accuracy expectation of 7.6 m (Zandbergen et al, ) and a level of completeness reflecting the content of the U.S. Census Bureau's Master Address File/TIGER database (https://www.census.gov/geo/reference/gtc/gtc_maftiger.html) on which all TIGER data are based. In 2011, after testing the accuracy of the 2010 TIGER road data, Los Angeles County used them as the basis for a new countywide address and street network file (https://egis3.lacounty.gov/dataportal/2011/04/25/2010‐tiger‐roads/).…”

A Photogrammetric Approach for Assessing Positional Accuracy of OpenStreetMap© Roads

“…Studies to describe the positional accuracy of geographical vector databases have been conducted where a test dataset is compared with a truth dataset of higher positional accuracy [19][20][21][22][23]. While other studies compared a test vector dataset with GPS locations [24,25] and positions determined from georeferenced orthoimagery [26].…”

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.…”