Visualizing digital traces for sustainable urban management: mapping tourism activity on the virtual public space
One of the challenges of heritage cities is sustainably balancing mass tourism and the daily life of its residents. Urban policies can modulate the impact of tourism through regulations focusing on areas with outstanding visitor pressure, which must consequently be delimited accurately and objective...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/359582 |
| Acceso en línea: | https://hdl.handle.net/2117/359582 https://dx.doi.org/10.3390/su13063159 |
| Access Level: | acceso abierto |
| Palabra clave: | Big data Geographic information systems Sustainable tourism - Spain - Barcelona Social media sustainable tourism data visualization social media spatial statistics cluster delimitation urban data data mining Barcelona big data geographic information science Dades massives Sistemes d'informació geogràfica Turisme sostenible - Catalunya - Barcelona Mitjans de comunicació social Àrees temàtiques de la UPC::Urbanisme::Impacte ambiental Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació |
| Sumario: | One of the challenges of heritage cities is sustainably balancing mass tourism and the daily life of its residents. Urban policies can modulate the impact of tourism through regulations focusing on areas with outstanding visitor pressure, which must consequently be delimited accurately and objectively. Within a traditionally data-scarce discipline, urban practitioners can currently employ a wide range of tracking technologies, but because of their limitations can also greatly benefit from new sources of data from social media. Using Barcelona as a testbed, a methodology is presented to identify and visualize hot spots of visitor activity using more than a million public geotagged images collected from the Flickr photo-sharing community. Multiple complementary visualization approaches are discussed that are suitable for different scales of analysis, from global to sub-block resolution. The presented methodology is firmly grounded in a well-established spatial statistics framework, adapted to a “big data” environment, to extract knowledge from social media. It is designed to generalize to other urban settings, providing substantial advantages over other surveying methods in terms of cost-efficiency, scalability, and accuracy, while capturing the behavior of a larger number of participants and covering more extensive areas or temporal spans. |
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