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Article: Mapping Residential Vacancies with Multisource Spatiotemporal Data: A Case Study in Beijing

TitleMapping Residential Vacancies with Multisource Spatiotemporal Data: A Case Study in Beijing
Authors
Li, XGong, P
Issue Date2022
PublisherMDPI. The Journal's web site is located at http://www.mdpi.com/journal/remotesensing/
Citation
Remote Sensing, 2022, v. 14, p. 376 How to Cite?
DOI: http://dx.doi.org/10.3390/rs14020376
Persistent Identifierhttp://hdl.handle.net/10722/319707
ISI Accession Number ID
WOS:000748226000001

 

DC FieldValueLanguage
dc.contributor.authorLi, X-
dc.contributor.authorGong, P-
dc.date.accessioned2022-10-14T05:18:15Z-
dc.date.available2022-10-14T05:18:15Z-
dc.date.issued2022-
dc.identifier.citationRemote Sensing, 2022, v. 14, p. 376-
dc.identifier.urihttp://hdl.handle.net/10722/319707-
dc.languageeng-
dc.publisherMDPI. The Journal's web site is located at http://www.mdpi.com/journal/remotesensing/-
dc.relation.ispartofRemote Sensing-
dc.titleMapping Residential Vacancies with Multisource Spatiotemporal Data: A Case Study in Beijing-
dc.typeArticle-
dc.identifier.emailGong, P: penggong@hku.hk-
dc.identifier.authorityGong, P=rp02780-
dc.identifier.doi10.3390/rs14020376-
dc.identifier.hkuros338891-
dc.identifier.volume14-
dc.identifier.spage376-
dc.identifier.epage376-
dc.identifier.isiWOS:000748226000001-

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