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A novel methodology for identifying environmental exposures using GPS data / Andreea Cetateanu in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1944 - 1960 Titre : A novel methodology for identifying environmental exposures using GPS data Type de document : Article/Communication Auteurs : Andreea Cetateanu, Auteur ; Bogdan-Alexandru Luca, Auteur ; Andrei Alin Popescu, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1944 - 1960 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données GPS [Termes IGN] durée de trajet [Termes IGN] santé [Termes IGN] véhicule automobile [Termes IGN] voisinage (relation topologique) Résumé : (Auteur) 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. Numéro de notice : A2016-572 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1145682 En ligne : http://dx.doi.org/10.1080/13658816.2016.1145682 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81728 [article]

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