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dc.contributor.advisorBryan, Karin R.
dc.contributor.authorMay-Stanley, Bridgette Petra
dc.date.accessioned2022-06-17T01:08:42Z
dc.date.available2022-06-17T01:08:42Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/10289/14929
dc.description.abstractResearch that gathers data from public reporting is susceptible to population bias, which arises from a lack of knowledge on the probability of a person’s ability to witness an event. Data collection based on public reporting is often used in coastal research relating to litter, stranded marine animals or bird spotting. It is biased by the probability of a person being in the vicinity, noticing and informing the appropriate organizations about the event. There is potential to improve population biased data by correcting for the probability of a person being present in a particular coastal vicinity. This thesis aims to better understand spatial and temporal beach usage at Tairua Beach in New Zealand. Building on existing literature, this research incorporates modern techniques to detect people on beaches from images taken every hour, during daylight, over a six-year period (2008 to 2013) from Tairua Beach, New Zealand. These methods include histogram matching, signal detection, machine learning-based classification, image registration and rectification, and various data cleaning techniques. Analysis of the data showed that patterns of beach usage varied on scales of hours, days, months, seasons, and years, and variations followed general expected trends, such as there were more beach users over weekends and summer, reported in the literature. However, annual variations in beach usage did not behave as expected, having a couple of extreme values, likely caused by a change in camera equipment that improved image quality. Annual variations in beach usage were distributed spatially in a way that reflected changes in beach morphology, particularly in 2008 to 2010. Interpretation of spatial patterns in beach usage was obscured by resolution bias that required correction. Images were taken from a fixed position east of Tairua Beach with a scope of approximately 1.2 km of beach area. Naturally, the east end, which was closest to the camera, had higher resolution thus more people were detected on that end of the beach. The relative probability that someone occupied a position on the beach was derived from spatial distribution of the number of people counted in each image.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherThe University of Waikato
dc.rightsAll items in Research Commons are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectRemote Sensing
dc.subjectTairua Beach
dc.subjectBeach Usage
dc.subjectCoastal Monitoring
dc.subject.lcshBeaches -- Monitoring -- New Zealand -- Tairua Beach
dc.subject.lcshCoastal zone management -- New Zealand -- Tairua Beach
dc.subject.lcshBeaches -- New Zealand -- Tairua Beach -- Usage
dc.subject.lcshTairua Beach (N.Z.) -- Environmental aspects
dc.subject.lcshRemote sensing -- New Zealand -- Tairua Beach
dc.subject.lcshTairua Beach (N.Z.) -- Population -- Monitoring
dc.titleRemote coastal monitoring of beach usage on Tairua Beach
dc.typeThesis
thesis.degree.grantorThe University of Waikato
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (Research) (MSc(Research))
dc.date.updated2022-05-27T00:50:35Z
pubs.place-of-publicationHamilton, New Zealanden_NZ


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