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dc.contributor.authorGarcia, Rodrigo Alejandro
dc.contributor.supervisorDr Peter Fearns
dc.contributor.supervisorDr John Hedley
dc.date.accessioned2017-01-30T10:07:05Z
dc.date.available2017-01-30T10:07:05Z
dc.date.created2016-02-18T07:31:49Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/20.500.11937/1458
dc.description.abstract

Propagating the inherent uncertainty in hyperspectral remote sensing is key in understanding the limitation and potential of derived bathymetry and benthic classification. Using an improved optimisation algorithm, the potential of detecting temporal bathymetric changes above uncertainty was quantified from a time series of hyperspectral imagery. A new processing approach was also developed that assessed the limitations and potential of benthic classification by analysing optical separability of substrates above total system uncertainty and attenuating water column.

dc.languageen
dc.publisherCurtin University
dc.titleUncertainty in Hyperspectral Remote Sensing: Analysis of the Potential and Limitation of Shallow Water Bathymetry and Benthic Classification
dc.typeThesis
dcterms.educationLevelPhD
curtin.departmentDepartment of Physics and Astronomy, Remote Sensing and Satellite Research Group
curtin.accessStatusOpen access


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