Improving Hyperspectral Image Consistency for Vegetation Classification over the Port Hedland Coastal Region
Access Status
Open access
Date
2020Supervisor
Brendan McGann
Peter Fearns
Type
Thesis
Award
PhD
Metadata
Show full item recordFaculty
Science and Engineering
School
Department of Imaging and Applied Physics
School of Physical Sciences
School of Electrical Engineering, Computing and Mathematical Sciences (EECMS)
Collection
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.