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Analysis of human mobility patterns from GPS trajectories and contextual information / Katarzyna Siła-Nowicka in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 881 - 906 Titre : Analysis of human mobility patterns from GPS trajectories and contextual information Type de document : Article/Communication Auteurs : Katarzyna Siła-Nowicka, Auteur ; Jan Vandrol, Auteur ; Taylor Oshan, Auteur Année de publication : 2016 Article en page(s) : pp 881 - 906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] comportement [Termes IGN] données localisées des bénévoles [Termes IGN] exploration de données [Termes IGN] itinéraire [Termes IGN] milieu urbain [Termes IGN] mobilité humaine [Termes IGN] modèle numérique [Termes IGN] plan de déplacement urbain [Termes IGN] positionnement par GPS [Termes IGN] prise en compte du contexte [Termes IGN] segmentation dynamique Résumé : (Auteur) Human mobility is important for understanding the evolution of size and structure of urban areas, the spatial distribution of facilities, and the provision of transportation services. Until recently, exploring human mobility in detail was challenging because data collection methods consisted of cumbersome manual travel surveys, space-time diaries, or interviews. The development of location-aware sensors has significantly altered the possibilities for acquiring detailed data on human movements. Although this has spurred many methodological developments in identifying human movement patterns, many of these methods operate solely from the analytical perspective and ignore the environmental context within which the movement takes place. In this paper, we attempt to widen this view and present an integrated approach to the analysis of human mobility using a combination of volunteered GPS trajectories and contextual spatial information. We propose a new framework for the identification of dynamic (travel modes) and static (significant places) behaviour using trajectory segmentation, data mining, and spatio-temporal analysis. We are interested in examining if and how travel modes depend on the residential location, age, or gender of the tracked individuals. Further, we explore theorised ‘third places’, which are spaces beyond main locations (home/work) where individuals spend time to socialise. Can these places be identified from GPS traces? We evaluate our framework using a collection of trajectories from 205 volunteers linked to contextual spatial information on the types of places visited and the transport routes they use. The result of this study is a contextually enriched data set that supports new possibilities for modelling human movement behaviour. Numéro de notice : A2016-288 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1100731 En ligne : https://doi.org/10.1080/13658816.2015.1100731 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80867 [article]

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