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dc.contributor.authorAllan, Mathew Granten_NZ
dc.date.accessioned2008-02-22T14:55:24Z
dc.date.available2009-02-12T15:59:08Z
dc.date.issued2008en_NZ
dc.identifier.citationAllan, M. G. (2008). Remote Sensing of Water Quality in Rotorua and Waikato Lakes (Thesis, Master of Science (MSc)). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/2292en
dc.identifier.urihttps://hdl.handle.net/10289/2292
dc.description.abstractRemote sensing has the potential to monitor spatial variation in water quality over large areas. While ocean colour work has developed analytical bio-optical water quality retrieval algorithms for medium spatial resolution platforms, remote sensing of lake water is often limited to high spatial resolution satellites such as Landsat, which have limited spectral resolution. This thesis presents the results of an investigation into satellite monitoring of lake water quality. The aim of this investigation was to ascertain the feasibility of estimating water quality and its spatial distribution using Landsat 7 ETM+ imagery combined with in situ data from Rotorua and Waikato lakes. For the comparatively deep Rotorua lakes, r² values of 0.91 (January 2002) and 0.83 (March 2002) were found between in situ chlorophyll (chl) a and the Band1/Band3 ratio. This technique proved useful for analysing the spatial distribution of phytoplankton, especially in lakes Rotoiti and Rotoehu. For the more bio-optically complex shallow lakes of the Waikato, a linear spectral unmixing (LSU) approach was investigated where the water surface reflectance spectrum is defined by the contribution from pure pixels or endmembers. The model estimates the percentage of the endmember within the pixel, which is then used in a final regression with in situ data to map water quality in all pixels. This approach was used to estimate the concentration of chl a (r² = 0.84). Total suspended solid (TSS) concentration was mapped using the traditional Band 3 regression with in situ data, which combined atmospherically corrected reflectance for both images into a single relationship (r² = 0.98). The time difference between in situ data collection and satellite data capture is a potential source of error. Other potential sources of error include sample location accuracy, the influence of dissolved organic matter, and masking of chl a signatures by high concentrations of TSS. The results from this investigation suggest that remote sensing of water quality provides meaningful and useful information with a range of applications and could provide information on temporal spatial variability in water quality.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherThe University of Waikatoen_NZ
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 sensingen_NZ
dc.subjectwater qualityen_NZ
dc.subjectlandsaten_NZ
dc.subjectlinear spectral unmixingen_NZ
dc.titleRemote Sensing of Water Quality in Rotorua and Waikato Lakesen_NZ
dc.typeThesisen_NZ
thesis.degree.disciplineSchool of Science and Engineeringen_NZ
thesis.degree.grantorUniversity of Waikatoen_NZ
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (MSc)en_NZ
uow.date.accession2008-02-22T14:55:24Zen_NZ
uow.date.available2009-02-12T15:59:08Zen_NZ
uow.identifier.adthttp://adt.waikato.ac.nz/public/adt-uow20080222.145524en_NZ
uow.date.migrated2009-06-09T23:29:19Zen_NZ
pubs.elements-id55701
pubs.place-of-publicationHamilton, New Zealanden_NZ


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