Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/107684
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dc.contributor.authorFonte, C. C.-
dc.contributor.authorMinghini, M.-
dc.contributor.authorAntoniou, V.-
dc.contributor.authorPatriarca, J.-
dc.contributor.authorSee, L.-
dc.date.accessioned2023-07-27T08:15:24Z-
dc.date.available2023-07-27T08:15:24Z-
dc.date.issued2018-
dc.identifier.issn2194-9034pt
dc.identifier.urihttps://hdl.handle.net/10316/107684-
dc.description.abstractThis paper examines the feasibility of using data from OpenStreetMap (OSM), Facebook and Foursquare as a source of information on the function of buildings. Such information is rarely openly available and if available, would vary between cities by nomenclature, making comparisons between places difficult. Volunteered Geographic Information (VGI) including data from social media represents new potential sources of building function data that have not yet been exploited for this purpose. Using a part of the city of Milan as the study area, building data from OSM and points of interest (POIs) from OSM, Facebook and Foursquare were extracted to derive the building function. This resulted in the classification of building function for more than 80% of the buildings and demonstrated that both Facebook and Foursquare can complement the building function derived from OSM, helping to fill in missing gaps. This preliminary study has demonstrated the potential of this approach for deriving building function information from open data in a simple way yet still requires independent validation with alternative sources as well as extension to other areas that have different amounts of OSM and social media coverage.pt
dc.language.isoengpt
dc.publisherInternational Society for Photogrammetry and Remote Sensingpt
dc.relationUID/MULTI/ 00308/2013pt
dc.relationFP7 ERC project CrowdLand (No. 617754)pt
dc.relationHorizon2020 LandSense project (No. 689812)pt
dc.relationURBAN-GEO BIG DATA, a Project of National Interest (PRIN) funded by the Italian Ministry of Education, University and Research (No. 20159CNLW8)pt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectVolunteered Geographic Informationpt
dc.subjectOpenStreetMappt
dc.subjectFacebookpt
dc.subjectFoursquarept
dc.subjectBuilding Functionpt
dc.subjectAutomated Classificationpt
dc.titleClassification of building function using available sources of VGIpt
dc.typearticle-
degois.publication.firstPage209pt
degois.publication.lastPage215pt
degois.publication.issue4pt
degois.publication.titleInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archivespt
dc.peerreviewedyespt
dc.identifier.doi10.5194/isprs-archives-XLII-4-209-2018pt
degois.publication.volume42pt
dc.date.embargo2018-01-01*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCom Texto completo-
crisitem.author.researchunitINESC Coimbra – Institute for Systems Engineering and Computers at Coimbra-
crisitem.author.orcid0000-0001-9408-8100-
Appears in Collections:I&D INESCC - Artigos em Revistas Internacionais
FCTUC Matemática - Artigos em Revistas Internacionais
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