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Landscape characterization using photographs from crowdsourced platforms: content analysis of social media photographs

  • Dades identificatives

    Identificador: imarina:5899369
    Autors:
    Callau A, Albert M, Rota J, Giné D
    Resum:
    Landscape characterisation using social media photographs from popular platforms has been proposed as a landscape and ecosystem services approach. However, popular crowdsourced websites provide uncharacterized data and are only representative of the general public. Photographs from crowdsourced sports platforms, whose users are more homogeneous, could help to characterise landscape more uniformly. In this study we use automated content analysis from photographs on Wikiloc, a crowdsourced sports platform, to characterize landscape in the Ebro Delta Natural Park, a protected area in Spain. Our approach applies big data procedures and spatial analysis to provide in-depth information regarding what draws visitors' attention to a landscape and to ascertain their intrasite flow. Our results show that sports users are keen on natural landscapes and pay less attention to rural and degraded landscapes, and that areas closer to paths are more photographed than more distant areas.
  • Altres:

    Autor segons l'article: Callau A, Albert M, Rota J, Giné D
    Departament: Geografia
    Autor/s de la URV: Avila Callau, Aitor / Perez Albert, Maria Yolanda / SERRANO GINÉ, DAVID
    Resum: Landscape characterisation using social media photographs from popular platforms has been proposed as a landscape and ecosystem services approach. However, popular crowdsourced websites provide uncharacterized data and are only representative of the general public. Photographs from crowdsourced sports platforms, whose users are more homogeneous, could help to characterise landscape more uniformly. In this study we use automated content analysis from photographs on Wikiloc, a crowdsourced sports platform, to characterize landscape in the Ebro Delta Natural Park, a protected area in Spain. Our approach applies big data procedures and spatial analysis to provide in-depth information regarding what draws visitors' attention to a landscape and to ascertain their intrasite flow. Our results show that sports users are keen on natural landscapes and pay less attention to rural and degraded landscapes, and that areas closer to paths are more photographed than more distant areas.
    Grup de recerca: GRATET. Anàlisi Territorial i Estudis Turístics
    Àrees temàtiques: Interdisciplinar Geosciences, multidisciplinary Geociências General earth and planetary sciences Environmental science (miscellaneous) Engenharias ii Earth and planetary sciences (miscellaneous) Earth and planetary sciences (all)
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 23915447
    Adreça de correu electrònic de l'autor: aitor.avila@urv.cat aitor.avila@urv.cat aitor.avila@urv.cat myolanda.perez@urv.cat
    Identificador de l'autor: 0000-0003-1634-4986
    Data d'alta del registre: 2024-09-21
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Open Geosciences. 11 (1): 558-571
    Referència de l'ítem segons les normes APA: Callau A, Albert M, Rota J, Giné D (2019). Landscape characterization using photographs from crowdsourced platforms: content analysis of social media photographs. Open Geosciences, 11(1), 558-571. DOI: 10.1515/geo-2019-0046
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2019
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Earth and Planetary Sciences (Miscellaneous),Environmental Science (Miscellaneous),Geosciences, Multidisciplinary
    Interdisciplinar
    Geosciences, multidisciplinary
    Geociências
    General earth and planetary sciences
    Environmental science (miscellaneous)
    Engenharias ii
    Earth and planetary sciences (miscellaneous)
    Earth and planetary sciences (all)
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