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

Includes abstract. === Includes bibliographical references. === 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 physi...

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Bibliographic Details
Main Author: Williamson, Robert I
Other Authors: Field, John G
Format: Doctoral Thesis
Language:English
Published: University of Cape Town 2014
Subjects:
Online Access:http://hdl.handle.net/11427/6444
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-uct-oai-localhost-11427-64442020-07-22T05:07:28Z Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study Williamson, Robert I Field, John G Shillington, Frank Jarre, Astrid Potgieter, Anet Oceanography Includes abstract. Includes bibliographical references. 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. 2014-08-13T19:43:15Z 2014-08-13T19:43:15Z 2013 Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/6444 eng application/pdf University of Cape Town Faculty of Science Department of Oceanography
collection NDLTD
language English
format Doctoral Thesis
sources NDLTD
topic Oceanography
spellingShingle Oceanography
Williamson, Robert 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
description Includes abstract. === Includes bibliographical references. === 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.
author2 Field, John G
author_facet Field, John G
Williamson, Robert I
author Williamson, Robert I
author_sort Williamson, Robert I
title Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study
title_short Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study
title_full Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study
title_fullStr Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study
title_full_unstemmed Estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern Benguela case study
title_sort estimating the spatial and temporal variability of primary production from a combination of in situ and remote sensing data a southern benguela case study
publisher University of Cape Town
publishDate 2014
url http://hdl.handle.net/11427/6444
work_keys_str_mv AT williamsonroberti estimatingthespatialandtemporalvariabilityofprimaryproductionfromacombinationofinsituandremotesensingdataasouthernbenguelacasestudy
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