Separation of Soil-Plant Spectral Mixtures by Factor Analysis

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dc.contributor.author Huete, Alfredo en_US
dc.contributor.editor en_US
dc.date.accessioned 2011-02-07T06:23:16Z
dc.date.available 2011-02-07T06:23:16Z
dc.date.issued 1986 en_US
dc.identifier 2009001558 en_US
dc.identifier.citation Huete Alfredo 1986, 'Separation of Soil-Plant Spectral Mixtures by Factor Analysis', Elsevier, vol. 19, no. 3, pp. 237-251. en_US
dc.identifier.issn 0034-4257 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13622
dc.description.abstract A factor-analytic inversion model is presented which enables a data set of spectral mixtures to be decomposed into the sum of unique reflecting components weighted by their corresponding amounts. Spectral mixtures are decomposed into abstract eigenspectra and eigenvector matrices. The eigenspectra are then transformed into pure component spectral signatures through a target testing procedure that allows one to individually search for the presence of ground reflecting features. Soil-plant mixtures with variable soil moisture and plant densities were successfully decomposed into dry soil, wet soil, and vegetation components and their respective amounts in all spectral mixtures were determined. Potential uses of factor analysis in soil identification and biomass assessment are discusse en_US
dc.language en_US
dc.publisher Elsevier en_US
dc.relation.isbasedon http://dx.doi.org/10.1016/0034-4257(86)90055-6 en_US
dc.title Separation of Soil-Plant Spectral Mixtures by Factor Analysis en_US
dc.parent Remote Sensing Of Environment en_US
dc.journal.volume 19 en_US
dc.journal.number 3 en_US
dc.publocation United States en_US
dc.identifier.startpage 237 en_US
dc.identifier.endpage 251 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 090900 en_US
dc.personcode 108636 en_US
dc.percentage 100 en_US
dc.classification.name Geomatic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US
dc.staffid 108636 en_US


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