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dc.contributor.authorAgnello, Jennie M.en_US
dc.date.accessioned2014-03-14T21:49:32Z
dc.date.available2014-03-14T21:49:32Z
dc.date.issued1987-08-05en_US
dc.identifier.otheretd-11142012-040055en_US
dc.identifier.urihttp://hdl.handle.net/10919/45649
dc.description.abstract

Although the maximum likelihood classifier is a popular classification technique, there is an inherent problem associated with the 100% classification of a scene. This is because there will inevitably be pixels within a study area that have a low probability of belonging to any of the predefined categories.

The focus of this research was to locate these low probability pixels and observe their affect on classification accuracy. This was done by performing supervised classifications at various threshold levels using two methods of classification training combined category training site statistics and separated category training site statistics. In general, it was found that a majority of the scene was classified at very low probabilities but the accuracy of the resulting classifications was much greater than the low probabilities would suggest.

en_US
dc.format.mediumBTDen_US
dc.publisherVirginia Techen_US
dc.relation.haspartLD5655.V855_1987.A384.pdfen_US
dc.subjectWetlandsen_US
dc.subject.lccLD5655.V855 1987.A384en_US
dc.titleThe effect of thresholding a maximum likelihood classifier on the accuracy of a landsat classification of a forested wetlanden_US
dc.typeThesisen_US
dc.contributor.departmentForestryen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineForestryen_US
dc.contributor.committeechairSmith, James L.en_US
dc.contributor.committeememberCampbell, James B. Jr.en_US
dc.contributor.committeememberJohnson, Steven D.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11142012-040055/en_US
dc.date.sdate2012-11-14en_US
dc.date.rdate2012-11-14
dc.date.adate2012-11-14en_US


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