The context of outdoor walking: A classification of user‐generated routes.
Leisure walking has known benefits to public health, from both physical and psychological viewpoints. Complementing traditional print information sources, dedicated online platforms and apps provide tools to search, discover, plan and share routes. While walking routes are highly heterogeneous in te...
| Publicado en: | Geographical Journal Vol. 189; no. 3; pp. 485 - 501 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
Sep2023
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=169914749&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 169914749 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00167398 GEO jtl: Geographical Journal issn: 00167398 maglogo: Y pubinfo: dt: Sep2023 vid: 189 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 169914749 10.1111/geoj.12511 ppf: 485 ppct: 16 formats: fmt: – @attributes: type: T db: hlh ui: 169914749 – @attributes: type: C db: hlh ui: 169914749 – @attributes: type: P db: hlh ui: 169914749 tig: atl: The context of outdoor walking: A classification of user‐generated routes. aug: au: Ballatore, Andrea Cavazzi, Stefano Morley, Jeremy affil: Department of Digital Humanities, King's College London, London, UK Ordnance Survey, Southampton, UK su: United Kingdom Information resources Focus groups Land cover Classification User-generated content sug: subj: Information resources Focus groups United Kingdom Land cover Classification User-generated content keyword: Great Britain leisure walking recreational walking route classification user‐generated content walking routes Great Britain leisure walking recreational walking route classification user‐generated content walking routes ab: Leisure walking has known benefits to public health, from both physical and psychological viewpoints. Complementing traditional print information sources, dedicated online platforms and apps provide tools to search, discover, plan and share routes. While walking routes are highly heterogeneous in terms of their properties and geographical context, current platforms adopt simple representations of basic attributes. In this article, we report on a research project at the Ordnance Survey on the representation and recommendation of walking routes, which comprises the following contributions. Firstly, we outline a theoretical framework of leisure walking, intersecting its individual, social and environmental dimensions. Secondly, analysing about 4 million user‐generated walking routes produced in Great Britain, we characterise routes combining primary attributes and contextual information, including land cover and points of interest. Thirdly, by applying unsupervised learning to this data model, we produce the Walking Route Classification. This classification is methodologically similar to geo‐demographic classifications and identifies groups and supergroups of similar routes in a large multidimensional attribute space. This body of work is evaluated through a survey and a focus group with experts, showing encouraging results. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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