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Pàgina inicial > Articles > Articles publicats > A tag is worth a thousand pictures : |
Data: | 2022 |
Resum: | Environmental values depend on social-ecological interactions and, in turn, influence the production of the underlying biophysical ecosystems. Understanding the nuanced nature of the values that humans ascribe to the environment is thus a key frontier for environmental science and planning. The development of many of these values depends on social-ecological interactions, such as outdoor recreation, landscape aesthetic appreciation or educational experiences with and within nature that can be articulated through the framework of cultural ecosystem services (CES). However, the non-material and intangible nature of CES has challenged previous attempts to assess the multiple and subjective values that people attach to them. In particular, this study focuses on assessing relational values ascribed to CES, here defined as values resonating with core principles of justice, reciprocity, care, and responsibility towards humans and more-than-humans. Building on emerging approaches for inferring relational CES values through social media (SM) images, this research explores the additional potential of a combined analysis of both the visual and textual content of SM data. To do so, we developed an inductive, empirically grounded coding protocol as well as a values typology that could be iteratively tested and verified by three different researchers to improve the consistency and replicability of the assessment. As a case study, we collected images and texts shared on the photo-sharing platform Flickr between 2004 and 2017 that were geotagged within the peri-urban park of Collserola, at the outskirts of Barcelona, Spain. Results reveal a wide spectrum of nine CES values within the park boundaries that show positive and negative correlations among each other, providing useful information for landscape planning and management. Moreover, the study highlights the need for spatial, temporal and demographic analysis, as well as for supervised machine learning techniques to further leverage SM data into contextual and just decision-making and planning. |
Ajuts: | Ministerio de Ciencia e Innovación PCIN-2016-002 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-775 Agència de Gestió d'Ajuts Universitaris i de Recerca 2018FI_B00635 European Commission 818002 European Commission 869324 European Commission 730243 Ministerio de Ciencia e Innovación CEX2019-000940-M |
Nota: | Altres ajuts: acords transformatius de la UAB |
Nota: | Unidad de excelencia María de Maeztu CEX2019-000940-M |
Drets: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. |
Llengua: | Anglès |
Document: | Article ; recerca ; Versió publicada |
Matèria: | Cultural ecosystem services ; Empirically grounded values typology ; Landscape planning and management ; Relational values ; Social media data analysis |
Publicat a: | Ecosystem services, Vol. 58 (December 2022) , art. 101495, ISSN 2212-0416 |
16 p, 1.5 MB |