A novel methodology for identifying environmental exposures using GPS data. Issue 10 (2nd October 2016)
- Record Type:
- Journal Article
- Title:
- A novel methodology for identifying environmental exposures using GPS data. Issue 10 (2nd October 2016)
- Main Title:
- A novel methodology for identifying environmental exposures using GPS data
- Authors:
- Cetateanu, Andreea
Luca, Bogdan-Alexandru
Popescu, Andrei Alin
Page, Angie
Cooper, Ashley
Jones, Andy - Abstract:
- ABSTRACT: Aim : While studies using global positioning systems (GPS) have the potential to refine measures of exposure to the neighbourhood environment in health research, one limitation is that they do not typically identify time spent undertaking journeys in motorised vehicles when contact with the environment is reduced. This paper presents and tests a novel methodology to explore the impact of this concern. Methods : Using a case study of exposure assessment to food environments, an unsupervised computational algorithm is employed in order to infer two travel modes: motorised and non-motorised, on the basis of which trips were extracted. Additional criteria are imposed in order to improve robustness of the algorithm. Results : After removing noise in the GPS data and motorised vehicle journeys, 82.43% of the initial GPS points remained. In addition, after comparing a sub-sample of trips classified visually of motorised, non-motorised and mixed mode trips with the algorithm classifications, it was found that there was an agreement of 88%. The measures of exposure to the food environment calculated before and after algorithm classification were strongly correlated. Conclusion : Identifying non-motorised exposures to the food environment makes little difference to exposure estimates in urban children but might be important for adults or rural populations who spend more time in motorised vehicles.
- Is Part Of:
- International journal of geographical information science. Volume 30:Issue 10(2016)
- Journal:
- International journal of geographical information science
- Issue:
- Volume 30:Issue 10(2016)
- Issue Display:
- Volume 30, Issue 10 (2016)
- Year:
- 2016
- Volume:
- 30
- Issue:
- 10
- Issue Sort Value:
- 2016-0030-0010-0000
- Page Start:
- 1944
- Page End:
- 1960
- Publication Date:
- 2016-10-02
- Subjects:
- Global positioning systems -- food environments -- travel mode -- unsupervised algorithm
Geography -- Data processing -- Periodicals
Information storage and retrieval systems -- Periodicals
Géomatique -- Périodiques
Systèmes d'information -- Périodiques
910.285 - Journal URLs:
- http://www.tandfonline.com/loi/tgis20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/13658816.2016.1145682 ↗
- Languages:
- English
- ISSNs:
- 1365-8816
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.266150
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7426.xml