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Article: VIIRS-based remote sensing estimation of ground-level PM2.5 concentrations in Beijing–Tianjin–Hebei: A spatiotemporal statistical model

TitleVIIRS-based remote sensing estimation of ground-level PM2.5 concentrations in Beijing–Tianjin–Hebei: A spatiotemporal statistical model
Authors
Wu, JYao, FLi, WSi, M
KeywordsBeijing–Tianjin–Hebei
Geographically weighted regression
NO2
PM2.5
Time fixed effects regression model
VIIRS AOD
Issue Date2016
Citation
Remote Sensing of Environment, 2016, v. 184, p. 316-328 How to Cite?
DOI: http://dx.doi.org/10.1016/j.rse.2016.07.015
Persistent Identifierhttp://hdl.handle.net/10722/235395
ISI Accession Number ID
WOS:000383827800024

 

DC FieldValueLanguage
dc.contributor.authorWu, J-
dc.contributor.authorYao, F-
dc.contributor.authorLi, W-
dc.contributor.authorSi, M-
dc.date.accessioned2016-10-14T13:53:02Z-
dc.date.available2016-10-14T13:53:02Z-
dc.date.issued2016-
dc.identifier.citationRemote Sensing of Environment, 2016, v. 184, p. 316-328-
dc.identifier.urihttp://hdl.handle.net/10722/235395-
dc.languageeng-
dc.relation.ispartofRemote Sensing of Environment-
dc.subjectBeijing–Tianjin–Hebei-
dc.subjectGeographically weighted regression-
dc.subjectNO2-
dc.subjectPM2.5-
dc.subjectTime fixed effects regression model-
dc.subjectVIIRS AOD-
dc.titleVIIRS-based remote sensing estimation of ground-level PM2.5 concentrations in Beijing–Tianjin–Hebei: A spatiotemporal statistical model-
dc.typeArticle-
dc.identifier.emailLi, W: wfli@hku.hk-
dc.identifier.authorityLi, W=rp01507-
dc.identifier.doi10.1016/j.rse.2016.07.015-
dc.identifier.scopuseid_2-s2.0-84978924159-
dc.identifier.hkuros268331-
dc.identifier.volume184-
dc.identifier.spage316-
dc.identifier.epage328-
dc.identifier.isiWOS:000383827800024-

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