Academic Journal
Assessing the Accuracy and Completeness of OpenStreetMap Sidewalks: A Comparative Study With Google Street View.
| Τίτλος: | Assessing the Accuracy and Completeness of OpenStreetMap Sidewalks: A Comparative Study With Google Street View. |
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| Συγγραφείς: | Nichols BL; Department of Epidemiology and Biostatistics, West Virginia University School of Public Health, Morgantown, West Virginia., Groth C; Department of Epidemiology and Biostatistics, West Virginia University School of Public Health, Morgantown, West Virginia., Quinn TD; Department of Epidemiology and Biostatistics, West Virginia University School of Public Health, Morgantown, West Virginia. |
| Πηγή: | Preventing chronic disease [Prev Chronic Dis] 2026 Oct 01; Vol. 23, pp. E48. Date of Electronic Publication: 2026 Oct 01. |
| Τύπος έκδοσης: | Journal Article; Comparative Study; Research Support, N.I.H., Extramural |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion Country of Publication: United States NLM ID: 101205018 Publication Model: Electronic Cited Medium: Internet ISSN: 1545-1151 (Electronic) Linking ISSN: 15451151 NLM ISO Abbreviation: Prev Chronic Dis Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: [Atlanta, Ga.] : U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, [2004]- |
| Ιατρικοί όροι (MeSH): | Walking*/statistics & numerical data , Environment Design* , Geographic Information Systems*, Pedestrians/statistics & numerical data ; Humans ; Maryland ; Census Tract ; Population Density |
| Περίληψη: | Introduction: OpenStreetMap is an open-source and crowd-sourced geospatial database and one of the few available sources of sidewalk data for walkability research; however, its accuracy and completeness have not been systematically assessed. This study aimed to compare OpenStreetMap sidewalk data with Google Street View. Methods: We clipped an OpenStreetMap map of pedestrian-accessible roads in Maryland to 141 census tracts (~10.0% of census tracts in Maryland) using stratified random sampling across tertiles of population density. Fifty points within each census tract were randomly distributed across qualifying roads (n = 7,050). We determined sidewalk presence at each point in OpenStreetMap and Google Street View. We excluded points without Google Street View, resulting in a final sample of 6,103 points. In points with sidewalks in Google Street View (n = 3,674), logistic mixed effects models estimated odds of OpenStreetMap-Google Street View sidewalk agreement across population density tertiles and themes from the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI). Results: Of the total points (N = 6,103), 57.8% (3,530) indicated sidewalk agreement between OpenStreetMap and Google Street View. Agreement was 30.2% among points with sidewalks present in Google Street View. Among points with sidewalks (3,674) present in Google Street View, odds of sidewalk agreement were higher in mid-density tracts (odds ratio [OR], 2.43; 95% CI, 0.63-9.40) and high-density tracts (OR, 4.50, 95% CI, 1.16-17.38) than in low-density tracts. Tracts in which a racial and ethnic minority population was larger than the non-Hispanic White population had lower sidewalk agreement (OR, 0.11; 95% CI, 0.002-0.74); no other SVI theme was associated with agreement. Conclusion: While OpenStreetMap sidewalk data were generally accurate when available, the sidewalk data were incomplete, especially in areas with low population density or areas in which a non-Hispanic racial and ethnic minority population was larger than the White population. |
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| Grant Information: | U54 GM104942 United States GM NIGMS NIH HHS |
| Entry Date(s): | Date Created: 20261001 Date Completed: 20261001 Latest Revision: 20261009 |
| Update Code: | 20261010 |
| PubMed Central ID: | PMC13632927 |
| DOI: | 10.5888/pcd23.260255 |
| PMID: | 42821456 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1545-1151 |
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| DOI: | 10.5888/pcd23.260255 |