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Estimating phytoplankton size classes from their inherent optical properties
Phytoplankton plays a massive role in the regulation of greenhouse gases, with different functional types affecting the carbon cycle differently. The most practical way of synoptically mapping the ocean’s phytoplankton communities is through remote sensing with the aid of ocean-optics algorithms. Th...
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| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2020
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| _version_ | 1867613186825388032 |
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| access_status_str | Open Access |
| author | Berliner, David Stephen |
| author2 | Nicolls, Frederick |
| author_browse | Berliner, David Stephen Nicolls, Frederick |
| author_facet | Nicolls, Frederick Berliner, David Stephen |
| author_sort | Berliner, David Stephen |
| collection | Thesis |
| description | Phytoplankton plays a massive role in the regulation of greenhouse gases, with different functional types affecting the carbon cycle differently. The most practical way of synoptically mapping the ocean’s phytoplankton communities is through remote sensing with the aid of ocean-optics algorithms. This thesis is a study of the relationships between the Inherent Optical Properties (IOPs) of the ocean and the physical constituents within it, with a special focus on deriving phytoplankton size classes. Three separate models were developed, each focusing on a different relationship between absorption and phytoplankton size classes, before being combined into a final ensemble model. It was shown that all of the developed models performed better than the baseline model, which only estimates the mean values per size class, and that the results of the final ensemble model is comparable to, and performs better than, most other published models on the NOMAD dataset. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/31516 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:08.355Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/31516 Estimating phytoplankton size classes from their inherent optical properties Berliner, David Stephen Nicolls, Frederick Electrical Engineering Phytoplankton plays a massive role in the regulation of greenhouse gases, with different functional types affecting the carbon cycle differently. The most practical way of synoptically mapping the ocean’s phytoplankton communities is through remote sensing with the aid of ocean-optics algorithms. This thesis is a study of the relationships between the Inherent Optical Properties (IOPs) of the ocean and the physical constituents within it, with a special focus on deriving phytoplankton size classes. Three separate models were developed, each focusing on a different relationship between absorption and phytoplankton size classes, before being combined into a final ensemble model. It was shown that all of the developed models performed better than the baseline model, which only estimates the mean values per size class, and that the results of the final ensemble model is comparable to, and performs better than, most other published models on the NOMAD dataset. 2020-03-09T11:41:43Z 2020-03-09T11:41:43Z 2019 2020-03-09T07:37:25Z Master Thesis Masters MSc http://hdl.handle.net/11427/31516 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment |
| spellingShingle | Electrical Engineering Berliner, David Stephen Estimating phytoplankton size classes from their inherent optical properties |
| thesis_degree_str | Master's |
| title | Estimating phytoplankton size classes from their inherent optical properties |
| title_full | Estimating phytoplankton size classes from their inherent optical properties |
| title_fullStr | Estimating phytoplankton size classes from their inherent optical properties |
| title_full_unstemmed | Estimating phytoplankton size classes from their inherent optical properties |
| title_short | Estimating phytoplankton size classes from their inherent optical properties |
| title_sort | estimating phytoplankton size classes from their inherent optical properties |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/31516 |
| work_keys_str_mv | AT berlinerdavidstephen estimatingphytoplanktonsizeclassesfromtheirinherentopticalproperties |