Includes bibliographical references (p. 176-188). / An analytical framework for the simulation and quantitative interpretation of ocean colour data is presented, providing an inverse reflectance algorithm designed for the detection of harmful algal blooms. The adopted framework focuses on establishing quantitative relationships between optically important algal intracellular properties and inherent optical properties (IOPs), such as the absorption and backscattering coefficients, and the resultant effects on remote-sensing reflectance. A principal aim of the study is to establish the determinant variables of the IOPs associated with natural algal assemblages, and provide a means of simulating these IOPs. Algal size is an important determinant of optical properties, and the study demonstrates algal IOP simulation, using equivalent particle size distributions that can be simply parameterised with regard to effective cell diameter. Statistical analyses of causal variability are also conducted on absorption data from a variety of natural algal assemblages, revealing the relative importance of cell size, intracellular Chi a concentration, and accessory pigment complement. An improved understanding of algal angular scattering is regarded as key to the analytical modelling of ocean colour, and the use of two-layered spherical models for the simulation of algal scattering properties is investigated. Preliminary validation of the combined use of the equivalent size and two-layered models indicates that they are capable of adequately simulating the remote-sensing reflectance properties of high biomass bloom waters.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/6461 |
| Date | January 2005 |
| Creators | Bernard, Stewart |
| Contributors | Probyn, Trevor, Shillington, Frank |
| Publisher | University of Cape Town, Faculty of Science, Department of Oceanography |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, Doctoral, PhD |
| Format | application/pdf |
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