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dc.contributor.authorZou, L.
dc.contributor.authorSong, Yongze
dc.contributor.authorCervone, G.
dc.date.accessioned2025-06-23T01:00:00Z
dc.date.available2025-06-23T01:00:00Z
dc.date.issued2024
dc.identifier.citationZou, L. and Song, Y. and Cervone, G. 2024. Geospatial big data: theory, methods, and applications. Annals of GIS. 30 (4): pp. 411-415.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/97965
dc.identifier.doi10.1080/19475683.2024.2419749
dc.titleGeospatial big data: theory, methods, and applications
dc.typeJournal Article
dcterms.source.volume30
dcterms.source.number4
dcterms.source.startPage411
dcterms.source.endPage415
dcterms.source.issn1947-5683
dcterms.source.titleAnnals of GIS
dc.date.updated2025-06-23T00:59:59Z
curtin.departmentSchool of Design and the Built Environment
curtin.accessStatusIn process
curtin.facultyFaculty of Humanities
curtin.contributor.orcidSong, Yongze [0000-0003-3420-9622]
dcterms.source.eissn1947-5691
curtin.contributor.scopusauthoridSong, Yongze [57200073199]
curtin.repositoryagreementV3


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