Improving Geographically Weighted Regression Considering Directional Nonstationary for Ground-Level PM2.5 Estimation

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datacite.relatedItem.firstPage413
datacite.relatedItem.issue6
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleIJGI
datacite.relatedItem.volume10
dc.contributor.authorWeihao Xuan
dc.contributor.authorFeng Zhang
dc.contributor.authorHongye Zhou
dc.contributor.authorZhenhong Du
dc.contributor.authorRenyi Liu
dc.date.accessioned2025-05-14T12:40:40Z
dc.date.available2025-05-14T12:40:40Z
dc.date.issued2021
dc.identifier.doihttps://doi.org/10.3390/ijgi10060413
dc.identifier.otherjz000145-0409
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/21422
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleImproving Geographically Weighted Regression Considering Directional Nonstationary for Ground-Level PM2.5 Estimation
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/21423
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