Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data

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dc.contributor.advisorField, John Gen_ZA
dc.contributor.advisorReason, Chrisen_ZA
dc.contributor.authorWilliamson, Robert Ien_ZA
dc.date.accessioned2014-08-13T19:43:13Z
dc.date.available2014-08-13T19:43:13Z
dc.date.issued2007en_ZA
dc.descriptionIncludes bibliographical references (leaves 56-67).en_ZA
dc.description.abstractKnowledge of the vertical distribution of phytoplankton in the upper ocean is essential for accurate estimates of primary production. Satellite remote sensing has given scientists an unprecedented view of near-surface chlorophyll distribution and other surface conditions, including sea surface temperature and wind data, from regional to global scales but little information on the dynamics below the surface. As a result estimates of global production tend to use regional profile averages but these methods oversimplify the smaller scale dynamics, particularly in coastal regions where productivity is highly variable on time scales of weeks. A pilot study by computer science honours students in 2006 showed the viability of using a Dynamic Bayesian Network (DBN) in predicting a representative profile per pixel of a satellite map based on a database of time series satellite surface data. In this study, 5813 in situ profiles were obtained from the highly dynamic upwelling region around the southwestern coastline of southern Africa. The samples were collected between 1988 and 2006 between the coast and the continental slope. The region was divided into three sub-regions according to biophysical processes: the west Coast; the west Agulhas Bank; and the east Agulhas Bank. Of the 5813 profiles, 5557 were included in the sub-regions. Two consecutive processes were then applied to the profile database. First, the profiles were clustered using a k-means clustering program which produced 16 representative clusters.en_ZA
dc.identifier.apacitationWilliamson, R. I. (2007). <i>Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Oceanography. Retrieved from http://hdl.handle.net/11427/6443en_ZA
dc.identifier.chicagocitationWilliamson, Robert I. <i>"Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Oceanography, 2007. http://hdl.handle.net/11427/6443en_ZA
dc.identifier.citationWilliamson, R. 2007. Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Williamson, Robert I AB - Knowledge of the vertical distribution of phytoplankton in the upper ocean is essential for accurate estimates of primary production. Satellite remote sensing has given scientists an unprecedented view of near-surface chlorophyll distribution and other surface conditions, including sea surface temperature and wind data, from regional to global scales but little information on the dynamics below the surface. As a result estimates of global production tend to use regional profile averages but these methods oversimplify the smaller scale dynamics, particularly in coastal regions where productivity is highly variable on time scales of weeks. A pilot study by computer science honours students in 2006 showed the viability of using a Dynamic Bayesian Network (DBN) in predicting a representative profile per pixel of a satellite map based on a database of time series satellite surface data. In this study, 5813 in situ profiles were obtained from the highly dynamic upwelling region around the southwestern coastline of southern Africa. The samples were collected between 1988 and 2006 between the coast and the continental slope. The region was divided into three sub-regions according to biophysical processes: the west Coast; the west Agulhas Bank; and the east Agulhas Bank. Of the 5813 profiles, 5557 were included in the sub-regions. Two consecutive processes were then applied to the profile database. First, the profiles were clustered using a k-means clustering program which produced 16 representative clusters. DA - 2007 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data TI - Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data UR - http://hdl.handle.net/11427/6443 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/6443
dc.identifier.vancouvercitationWilliamson RI. Relating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface data. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Oceanography, 2007 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/6443en_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.otherApplied Marine Scienceen_ZA
dc.titleRelating an archive of in situ vertical chlorophyll-a profiles to concurrent remotely sensed surface dataen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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