{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T23:19:39Z","timestamp":1778109579430,"version":"3.51.4"},"reference-count":76,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2017,12,13]],"date-time":"2017-12-13T00:00:00Z","timestamp":1513123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>As cities become increasingly complex, Information and Communication Technologies (ICTs) bring smartness into organisations and communities, contributing to a more competitive tourism destination, i.e., smart tourism destinations. Enhanced information access coupled with a new kind of tourists avid for online content and predisposed to share information on social media, allows for a better understanding of tourist behaviour regarding their spatial distribution in urban destinations. Thus, smart tourism portrays individuals as information makers, refining the available alternatives for tracking their location. Big data analytics is a technology with the potential to develop Smart City services. From the analysis of the spatial distribution of tourists in the city of Lisbon based on data collected from the \u2018Panoramio\u2019 social network, we identify the most popular places in the city in a context of tourist visits. This new data largely contributes to understanding the consumption of space within urban tourist destinations and therefore enables us to differentiate the overcrowded places from the ones with potential to grow. This allows decision-makers to imagine new ways of planning and managing towards a sustainable \u2018smart\u2019 future.<\/jats:p>","DOI":"10.3390\/su9122317","type":"journal-article","created":{"date-parts":[[2017,12,14]],"date-time":"2017-12-14T04:30:55Z","timestamp":1513225855000},"page":"2317","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":102,"title":["Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7163-2641","authenticated-orcid":false,"given":"Luis","family":"Encalada","sequence":"first","affiliation":[{"name":"Institute of Geography and Spatial Planning, Universidade de Lisboa, Rua Branca Edm\u00e9e Marques, 1600-276 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9932-9241","authenticated-orcid":false,"given":"In\u00eas","family":"Boavida-Portugal","sequence":"additional","affiliation":[{"name":"Department of Spatial Planning and Environment, University of Groningen (RUG) P.O. Box 800, 9700 AV Groningen, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9105-2847","authenticated-orcid":false,"given":"Carlos","family":"Cardoso Ferreira","sequence":"additional","affiliation":[{"name":"Institute of Geography and Spatial Planning, Universidade de Lisboa, Rua Branca Edm\u00e9e Marques, 1600-276 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7228-6330","authenticated-orcid":false,"given":"Jorge","family":"Rocha","sequence":"additional","affiliation":[{"name":"Institute of Geography and Spatial Planning, Universidade de Lisboa, Rua Branca Edm\u00e9e Marques, 1600-276 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,13]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2015). World Urbanization Prospects: The 2014 Revision, United Nations. ST\/ESA\/SER.A\/366."},{"key":"ref_2","unstructured":"Organisation for Economic Co-operation and Development (OECD) (2012). OECD Environmental Outlook to 2050. 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