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dc.contributor.authorKong, Xin
dc.contributor.authorDorling, Steve
dc.date.accessioned2013-03-20T12:29:43Z
dc.date.available2013-03-20T12:29:43Z
dc.date.issued2008
dc.identifier.citationKong , X & Dorling , S 2008 , ' Near-surface soil moisture retrieval from ASAR Wide Swath imagery using a Principal Component Analysis ' , INTERNATIONAL JOURNAL OF REMOTE SENSING , vol. 29 , no. 10 , pp. 2925-2942 . https://doi.org/10.1080/01431160701442088
dc.identifier.issn0143-1161
dc.identifier.otherPURE: 1267326
dc.identifier.otherPURE UUID: c1283a0a-47ce-42b0-b799-9a03b54a141d
dc.identifier.otherScopus: 43149090985
dc.identifier.urihttp://hdl.handle.net/2299/10222
dc.description.abstractThe new ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) data provide good potential for routinely monitoring near surface soil moisture due to the increased temporal revisit capability compared with ERS2 SAR. In this paper, we propose a Principal Components Analysis (PCA) to retrieve near‐surface soil moisture from ASAR WSM data. The results demonstrate that PCA transformation can at least partially separate or group the effect factors, such as surface roughness, land cover, vegetation, and topography within the limitations of our datasets. The second principal component which was consistent with soil moisture and rainfall‐runoff dynamics was representative of the soil moisture Saturation Potential Index over a large area. Validation against field measurements and against the UK Met Office Surface Exchange Scheme shows the retrieval performs with reasonable accuracy.en
dc.language.isoeng
dc.relation.ispartofINTERNATIONAL JOURNAL OF REMOTE SENSING
dc.titleNear-surface soil moisture retrieval from ASAR Wide Swath imagery using a Principal Component Analysisen
dc.contributor.institutionSchool of Physics, Astronomy and Mathematics
dc.description.statusPeer reviewed
rioxxterms.versionofrecordhttps://doi.org/10.1080/01431160701442088
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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