CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI
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 diff...
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Format: | Article |
Language: | English |
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Copernicus Publications
2018-09-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4/209/2018/isprs-archives-XLII-4-209-2018.pdf |
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author | C. C. Fonte C. C. Fonte M. Minghini V. Antoniou J. Patriarca L. See |
author_facet | C. C. Fonte C. C. Fonte M. Minghini V. Antoniou J. Patriarca L. See |
author_sort | C. C. Fonte |
collection | DOAJ |
description | 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. |
first_indexed | 2024-12-10T18:04:58Z |
format | Article |
id | doaj.art-3ea059d72f054df0872edd318ac45575 |
institution | Directory Open Access Journal |
issn | 1682-1750 2194-9034 |
language | English |
last_indexed | 2024-12-10T18:04:58Z |
publishDate | 2018-09-01 |
publisher | Copernicus Publications |
record_format | Article |
series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
spelling | doaj.art-3ea059d72f054df0872edd318ac455752022-12-22T01:38:39ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-09-01XLII-420921510.5194/isprs-archives-XLII-4-209-2018CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGIC. C. Fonte0C. C. Fonte1M. Minghini2V. Antoniou3J. Patriarca4L. See5Department of Mathematics, University of Coimbra, Coimbra, PortugalInstitute for Systems Engineering and Computers at Coimbra (INESCC), Coimbra, PortugalDepartment of Civil and Environmental Engineering, Politecnico di Milano, Milan, ItalyGeographic Directorate, Hellenic Army General Staff, Athens, GreeceInstitute for Systems Engineering and Computers at Coimbra (INESCC), Coimbra, PortugalInternational Institute for Applied Systems Analysis, Laxenburg, AustriaThis 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.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4/209/2018/isprs-archives-XLII-4-209-2018.pdf |
spellingShingle | C. C. Fonte C. C. Fonte M. Minghini V. Antoniou J. Patriarca L. See CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
title | CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI |
title_full | CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI |
title_fullStr | CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI |
title_full_unstemmed | CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI |
title_short | CLASSIFICATION OF BUILDING FUNCTION USING AVAILABLE SOURCES OF VGI |
title_sort | classification of building function using available sources of vgi |
url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4/209/2018/isprs-archives-XLII-4-209-2018.pdf |
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