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dc.contributor.advisorBreen, Barbara
dc.contributor.authorZhang, ZhaoXuan
dc.date.accessioned2015-02-20T04:10:00Z
dc.date.available2015-02-20T04:10:00Z
dc.date.copyright2014
dc.date.created2015
dc.identifier.urihttp://hdl.handle.net/10292/8430
dc.description.abstractTraditional field-based methods of habitat mapping to determine and classify vegetation on private land have been proven unsatisfying in terms of coverage, and time and cost-effectiveness. Remote sensing using Unmanned Aerial Vehicles (UAVs) is a new technology which is able to acquire land resources and environmental gradients as well as other spatial information. Although research using UAV techniques has been active since the beginning of the 21st century in New Zealand, it still has tremendous potential value for further and deeper exploration of UAV use. There has been, to date, little academic research based on UAVs’ remote sensing apart from commercial and military use. The aim of this study was to develop effective UAV-based remote sensing methods to classify native New Zealand vegetation on private land using an easily accessible area of regenerating bush. Results of this research provide a systematic method for UAV remote sensing classification. The object-based maximum likelihood supervised classification produced the most accurate classification result of approximately 80% using the true colour imagery mosaic. The results of this thesis suggest that the UAV remote sensing technique is capable of acquiring sufficiently high quality data from private land that can be used to mosaic and produce accurate vegetation classification at a species level.en_NZ
dc.language.isoenen_NZ
dc.publisherAuckland University of Technology
dc.subjectRemote sensingen_NZ
dc.subjectUAVen_NZ
dc.subjectVegetation classificationen_NZ
dc.subjectSupervised classificationen_NZ
dc.subjectObject based classificationen_NZ
dc.subjectPix4Den_NZ
dc.titleNative vegetation classification using remote sensing techniques: a case study of dairy flat regrowth bush by using the AUT Unmanned Aerial Vehicleen_NZ
dc.typeThesis
thesis.degree.grantorAuckland University of Technology
thesis.degree.grantorAuckland University of Technology
thesis.degree.levelMasters Theses
thesis.degree.nameMaster of Applied Scienceen_NZ
thesis.degree.discipline
dc.rights.accessrightsOpenAccess
dc.date.updated2015-02-19T22:15:37Z


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