Literature DB >> 26154258

[Who Hits the Mark? A Comparative Study of the Free Geocoding Services of Google and OpenStreetMap].

D Lemke1, V Mattauch2, O Heidinger2, H W Hense1.   

Abstract

BACKGROUND: Geocoding, the process of converting textual information (addresses) into geographic coordinates is increasingly used in public health/epidemiological research and practice. To date, little attention has been paid to geocoding quality and its impact on different types of spatially-related health studies. The primary aim of this study was to compare 2 freely available geocoding services (Google and OpenStreetMap) with regard to matching rate (percentage of address records capable of being geocoded) and positional accuracy (distance between geocodes and the ground truth locations).
METHODS: Residential addresses were geocoded by the NRW state office for information and technology and were considered as reference data (gold standard). The gold standard included the coordinates, the quality of the addresses (4 categories), and a binary urbanity indicator based on the CORINE land cover data. 2 500 addresses were randomly sampled after stratification for address quality and urbanity indicator (approximately 20 000 addresses). These address samples were geocoded using the geocoding services from Google and OSM.
RESULTS: In general, both geocoding services showed a decrease in the matching rate with decreasing address quality and urbanity. Google showed consistently a higher completeness than OSM (>93 vs. >82%). Also, the cartographic confounding between urban and rural regions was less distinct with Google's geocoding API. Regarding the positional accuracy of the geo-coordinates, Google also showed the smallest deviations from the reference coordinates, with a median of <9 vs. <175.8 m. The cumulative density function derived from the positional accuracy showed for Google that nearly 95% and for OSM 50% of the addresses were geocoded within <50 m of their reference coordinates.
CONCLUSION: The geocoding API from Google is superior to OSM regarding completeness and positional accuracy of the geocoded addresses. On the other hand, Google has several restrictions, such as the limitation of the requests to 2 500 addresses per 24 h and the presentation of the results exclusively on Google Maps, which may complicate the use for scientific purposes. © Georg Thieme Verlag KG Stuttgart · New York.

Entities:  

Mesh:

Year:  2015        PMID: 26154258     DOI: 10.1055/s-0035-1549939

Source DB:  PubMed          Journal:  Gesundheitswesen        ISSN: 0941-3790


  4 in total

1.  Incorporating a location-based socioeconomic index into a de-identified i2b2 clinical data warehouse.

Authors:  Bret J Gardner; Jay G Pedersen; Mary E Campbell; James C McClay
Journal:  J Am Med Inform Assoc       Date:  2019-04-01       Impact factor: 4.497

2.  Quantifying simultaneous innovations in evolutionary medicine.

Authors:  Deryc T Painter; Frank van der Wouden; Manfred D Laubichler; Hyejin Youn
Journal:  Theory Biosci       Date:  2020-11-25       Impact factor: 1.919

3.  Using data from online geocoding services for the assessment of environmental obesogenic factors: a feasibility study.

Authors:  Maximilian Präger; Christoph Kurz; Julian Böhm; Michael Laxy; Werner Maier
Journal:  Int J Health Geogr       Date:  2019-06-07       Impact factor: 3.918

4.  Web Data Mining: Validity of Data from Google Earth for Food Retail Evaluation.

Authors:  Mariana Carvalho de Menezes; Vanderlei Pascoal de Matos; Maria de Fátima de Pina; Bruna Vieira de Lima Costa; Larissa Loures Mendes; Milene Cristine Pessoa; Paulo Roberto Borges de Souza-Junior; Amélia Augusta de Lima Friche; Waleska Teixeira Caiaffa; Letícia de Oliveira Cardoso
Journal:  J Urban Health       Date:  2020-11-23       Impact factor: 3.671

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.