Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX)

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dc.contributor.authorBechtel, Benjamin
dc.contributor.authorDemuzere, Matthias
dc.contributor.authorSismanidis, Panagiotis
dc.contributor.authorFenner, Daniel
dc.contributor.authorBrousse, Oscar
dc.contributor.authorBeck, Christoph
dc.contributor.authorVan Coillie, Frieke
dc.contributor.authorConrad, Olaf
dc.contributor.authorKeramitsoglou, Iphigenia
dc.contributor.authorMiddel, Ariane
dc.contributor.authorMills, Gerald
dc.contributor.authorNiyogi, Dev
dc.contributor.authorOtto, Marco
dc.contributor.authorSee, Linda
dc.contributor.authorVerdonck, Marie-Leen
dc.date.accessioned2019-08-02T08:00:17Z
dc.date.available2019-08-02T08:00:17Z
dc.date.issued2017-05-09
dc.date.updated2019-07-31T12:23:17Z
dc.description.abstractThe World Urban Database and Access Portal Tools (WUDAPT) is a community initiative to collect worldwide data on urban form (i.e., morphology, materials) and function (i.e., use and metabolism). This is achieved through crowdsourcing, which we define here as the collection of data by a bounded crowd, composed of students. In this process, training data for the classification of urban structures into Local Climate Zones (LCZ) are obtained, which are, like most volunteered geographic information initiatives, of unknown quality. In this study, we investigated the quality of 94 crowdsourced training datasets for ten cities, generated by 119 students from six universities. The results showed large discrepancies and the resulting LCZ maps were mostly of poor to moderate quality. This was due to general difficulties in the human interpretation of the (urban) landscape and in the understanding of the LCZ scheme. However, the quality of the LCZ maps improved with the number of training data revisions. As evidence for the wisdom of the crowd, improvements of up to 20% in overall accuracy were found when multiple training datasets were used together to create a single LCZ map. This improvement was greatest for small training datasets, saturating at about ten to fifteen sets.en
dc.description.sponsorshipDFG, 38787541, EXC 177: Integrierte Klimasystemanalyse und -vorhersageen
dc.description.sponsorshipEC/FP7/617754/EU/Harnessing the power of crowdsourcing to improve land cover and land-use information/CrowdLanden
dc.identifier.eissn2413-8851
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/9691
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-8731
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc551 Geologie, Hydrologie, Meteorologiede
dc.subject.otherLocal Climate Zonesen
dc.subject.otherurban climateen
dc.subject.othercrowdsourcingen
dc.subject.othervolunteered geographic informationen
dc.subject.otherclassificationen
dc.subject.otherWUDAPTen
dc.subject.otherLCZsen
dc.titleQuality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX)en
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber15en
dcterms.bibliographicCitation.doi10.3390/urbansci1020015en
dcterms.bibliographicCitation.issue2en
dcterms.bibliographicCitation.journaltitleUrban Scienceen
dcterms.bibliographicCitation.originalpublishernameMDPIen
dcterms.bibliographicCitation.originalpublisherplaceBaselen
dcterms.bibliographicCitation.volume1en
tub.accessrights.dnbfreeen
tub.affiliationFak. 6 Planen Bauen Umwelt::Inst. Ökologie::FG Klimatologiede
tub.affiliation.facultyFak. 6 Planen Bauen Umweltde
tub.affiliation.groupFG Klimatologiede
tub.affiliation.instituteInst. Ökologiede
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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