Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study

dc.contributor.advisorField, John Gen_ZA
dc.contributor.advisorShillington, Franken_ZA
dc.contributor.advisorJarre, Astriden_ZA
dc.contributor.advisorPotgieter, Aneten_ZA
dc.contributor.authorWilliamson, Robert Ien_ZA
dc.date.accessioned2014-08-13T19:43:15Z
dc.date.available2014-08-13T19:43:15Z
dc.date.issued2013en_ZA
dc.descriptionIncludes abstract.en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractThe aim of this thesis is to produce fine resolution estimates of primary production in three-dimensional space at the temporal scale that these events develop. It is hypothesized that complex relationships among time sequences of physical and biological processes that influence primary production can be automatically discovered from archives of data. This study uses an archive of in situ ship-board data containing subsurface temperature and phytoplankton distribution profiles. Each profile is associated in time and space with satellite remotely-sensed wind, sea surface temperature and surface chlorophyll a data. The bottom depth, season and location of each profile are also recorded. The archive of depth profiles is simplified by mapping each profile onto one of twelve representative profile clusters obtained using the k-means clustering algorithm so that each cluster contains a set of similar profiles and their corresponding data. Relationships between remotely sensed surface features and chlorophyll a profiles are first obtained from a static Bayesian network using same day data. This is then taken further by analysing time-series of satellite data to predict likely temperature and chlorophyll a profiles for each pixel of a 4 km resolution satellite image.en_ZA
dc.identifier.apacitationWilliamson, R. I. (2013). <i>Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Oceanography. Retrieved from http://hdl.handle.net/11427/6444en_ZA
dc.identifier.chicagocitationWilliamson, Robert I. <i>"Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Oceanography, 2013. http://hdl.handle.net/11427/6444en_ZA
dc.identifier.citationWilliamson, R. 2013. Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Williamson, Robert I AB - The aim of this thesis is to produce fine resolution estimates of primary production in three-dimensional space at the temporal scale that these events develop. It is hypothesized that complex relationships among time sequences of physical and biological processes that influence primary production can be automatically discovered from archives of data. This study uses an archive of in situ ship-board data containing subsurface temperature and phytoplankton distribution profiles. Each profile is associated in time and space with satellite remotely-sensed wind, sea surface temperature and surface chlorophyll a data. The bottom depth, season and location of each profile are also recorded. The archive of depth profiles is simplified by mapping each profile onto one of twelve representative profile clusters obtained using the k-means clustering algorithm so that each cluster contains a set of similar profiles and their corresponding data. Relationships between remotely sensed surface features and chlorophyll a profiles are first obtained from a static Bayesian network using same day data. This is then taken further by analysing time-series of satellite data to predict likely temperature and chlorophyll a profiles for each pixel of a 4 km resolution satellite image. DA - 2013 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2013 T1 - Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study TI - Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study UR - http://hdl.handle.net/11427/6444 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/6444
dc.identifier.vancouvercitationWilliamson RI. Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Oceanography, 2013 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/6444en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Oceanographyen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherOceanographyen_ZA
dc.titleEstimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case studyen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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