Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/107684
Title: Classification of building function using available sources of VGI
Authors: Fonte, C. C. 
Minghini, M.
Antoniou, V.
Patriarca, J. 
See, L.
Keywords: Volunteered Geographic Information; OpenStreetMap; Facebook; Foursquare; Building Function; Automated Classification
Issue Date: 2018
Publisher: International Society for Photogrammetry and Remote Sensing
Project: UID/MULTI/ 00308/2013 
FP7 ERC project CrowdLand (No. 617754) 
Horizon2020 LandSense project (No. 689812) 
URBAN-GEO BIG DATA, a Project of National Interest (PRIN) funded by the Italian Ministry of Education, University and Research (No. 20159CNLW8) 
Serial title, monograph or event: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume: 42
Issue: 4
Abstract: This 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.
URI: https://hdl.handle.net/10316/107684
ISSN: 2194-9034
DOI: 10.5194/isprs-archives-XLII-4-209-2018
Rights: openAccess
Appears in Collections:I&D INESCC - Artigos em Revistas Internacionais
FCTUC Matemática - Artigos em Revistas Internacionais

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