Using Open Street Map Data in Environmental Exposure Assessment Studies
Eastern Massachusetts, Bern Region, and South Israel as a Case Study
Bibliographic Data
| ID | 15464489 |
|---|---|
| Authors | Itai Kloog (0000-0003-1708-7440, Ben-Gurion University of the Negev, corresponding author), Lara Ifat Kaufman (Ben-Gurion University of the Negev), Kees de Hoogh (0000-0001-5974-2007, Swiss Tropical and Public Health Institute) |
| Year | 2018 |
| Volume | 15 |
| Issue | 11 |
| Pages | 2443-2443 |
| Publication date | 2018-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph15112443 |
| PMID | 30388884 |
| OpenAlex | W2899102993 |
| Language | EN |
| Citations received | 1 |
| References cited | 55 |
There is an increase in the awareness of the importance of spatial data in epidemiology and exposure assessment (EA) studies. Most studies use governmental and ordnance surveys, which are often expensive and sparsely updated, while in most developing countries, there are often no official geo-spatial data sources. OpenStreetMap (OSM) is an open source Volunteered Geographic Information (VGI) mapping project. Yet very few environmental epidemiological and EA studies have used OSM as a source for road data. Since VGI data is either noncommercial or governmental, the validity of OSM is often questioned. We investigate the robustness and validity of OSM data for use in epidemiological and EA studies. We compared OSM and Governmental Major Road Data (GRD) in three different regions: Massachusetts, USA; Bern, Switzerland; and Beer-Sheva, South Israel. The comparison was done by calculating data completeness, positional accuracy, and EA using traditional exposure methods. We found that OSM data is fairly complete and accurate in all regions. The results in all regions were robust, with Massachusetts showing the best fits (R2 0.93). Results in Bern (R2 0.78) and Beer-Sheva (R2 0.77) were only slightly lower. We conclude by suggesting that OSM data can be used reliably in environmental assessment studies
Cartography · Environmental epidemiology · Environmental health · Geographic information system · Geography · Open data · Remote sensing · Robustness (evolution · Spatial analysis · Volunteered Geographic Information · World Wide Web · Computer Science · Data-Driven Disease Surveillance · Geographic Information Systems Studies · Medicine · Urban Transport and Accessibility
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2021 - 2021 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |