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dc.contributor.authorBos, Shawn Henson
dc.contributor.supervisorBrendan McGannen_US
dc.contributor.supervisorPeter Fearnsen_US
dc.date.accessioned2021-02-10T00:49:27Z
dc.date.available2021-02-10T00:49:27Z
dc.date.issued2020en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/82565
dc.description.abstract

The brightness consistency of hyperspectral airborne data over the Port Hedland coastal region was improved through a newly developed mathematical-based technique termed normalisation. Classification of the normalised data resulted in improved spatially coherent vegetation structures, with particular emphasis on mangroves. In addition, spatial statistical analysis ensured the structures were well-defined to a suitable probability, which compared favourably to the results of an earlier commercial survey based on photointerpretation and field work.

en_US
dc.publisherCurtin Universityen_US
dc.titleImproving Hyperspectral Image Consistency for Vegetation Classification over the Port Hedland Coastal Regionen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentDepartment of Imaging and Applied Physicsen_US
curtin.departmentSchool of Physical Sciencesen_US
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciences (EECMS)
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidBos, Shawn Henson [0000-0002-2920-9364]en_US


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