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dc.contributor.authorHingee, Kassel Liam
dc.contributor.supervisorDr Peter Caccetta
dc.contributor.supervisorProf. Louis Caccetta
dc.date.accessioned2017-01-30T10:03:55Z
dc.date.available2017-01-30T10:03:55Z
dc.date.created2015-01-12T23:52:36Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/20.500.11937/1325
dc.description.abstract

This thesis presents methods that enable the generation of quantitative environmental indicators for remotely monitoring urban regions. Its contributions are a new morphological and surface fitting hybrid algorithm for the generation of ground elevation models, a vegetation classifier and significant research into Canonical Variate Analysis with Rational Polynomials (a feature extraction method that normalises the topographic illumination effect). These methods were tested on a 9600 square kilometre, 20cm resolution dataset covering Perth.

dc.languageen
dc.publisherCurtin University
dc.titleGround elevation models and land cover classifers for decimetre resolution urban monitoring
dc.typeThesis
dcterms.educationLevelMPhil
curtin.departmentSchool of Science, Department of Mathematics
curtin.accessStatusOpen access


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