{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/9023"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/9023","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Radiometric validation of multi-spectral ocean colour satellite data in high biomass Southern Benguela waters","abstract":"This study forms the first step towards a comprehensive ocean colour satellite validation strategy for the Southern Benguela region, and underlines the value of a statistical radiometric validation as a prerequisite to any geophysical validation exercise. A radiometric validation exercise was performed using co-incident MERIS RR data and in situ radiometer data from a mooring in the Southern Benguela near Lambert's Bay during the late summer bloom seasons of 2005 and 2006. The data are typified by very high biomass conditions. Sources of error associated with the in situ data are assessed and the magnitudes quantified. The satellite data is examined with particular reference to uncertainty derived from the atmospheric correction processes, which perform unreliably in many of the matchup instances. Results show that the accuracy of the atmospheric correction does not appear to be related to the in-water constituents and is more likely due to atmospheric variability or aerosol features that are not addressed in the models employed by the correction processes. It is also shown that while the radiometric data display a consistent bias in the red region of the spectrum, good correlation with the satellite measurements is observed here under high biomass conditions, underlining the importance of the red wavebands for coastal remote sensing. Recommendations towards the development of a comprehensive regional validation strategy include the establishment of low-cost measurement protocols for high biomass conditions, as well as further investigations into regional atmospheric variability to improve confidence in the atmospheric correction procedures.","abstract_html":"This study forms the first step towards a comprehensive ocean colour satellite validation strategy for the Southern Benguela region, and underlines the value of a statistical radiometric validation as a prerequisite to any geophysical validation exercise. A radiometric validation exercise was performed using co-incident MERIS RR data and in situ radiometer data from a mooring in the Southern Benguela near Lambert's Bay during the late summer bloom seasons of 2005 and 2006. The data are typified by very high biomass conditions. Sources of error associated with the in situ data are assessed and the magnitudes quantified. The satellite data is examined with particular reference to uncertainty derived from the atmospheric correction processes, which perform unreliably in many of the matchup instances. Results show that the accuracy of the atmospheric correction does not appear to be related to the in-water constituents and is more likely due to atmospheric variability or aerosol features that are not addressed in the models employed by the correction processes. It is also shown that while the radiometric data display a consistent bias in the red region of the spectrum, good correlation with the satellite measurements is observed here under high biomass conditions, underlining the importance of the red wavebands for coastal remote sensing. Recommendations towards the development of a comprehensive regional validation strategy include the establishment of low-cost measurement protocols for high biomass conditions, as well as further investigations into regional atmospheric variability to improve confidence in the atmospheric correction procedures.","abstract_has_math":false,"creators":["Robertson, Elisabeth"],"institution":"Department of Oceanography","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Bernard, Stewart","Shillington, Frank"],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009","date_published":"2009","updated_at":"2026-07-22T22:22:42Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/9023","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Bernard, Stewart","Shillington, Frank"]},{"key":"dc:creator","label":"Author","values":["Robertson, Elisabeth"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-10-31T18:06:49Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-10-31T18:06:49Z"]},{"key":"dc:date.issued","label":"Date","values":["2009"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Oceanography"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/9023"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes bibliographical references (leaves 106-117)."]},{"key":"dc:description.abstract","label":"Abstract","values":["This study forms the first step towards a comprehensive ocean colour satellite validation strategy for the Southern Benguela region, and underlines the value of a statistical radiometric validation as a prerequisite to any geophysical validation exercise. A radiometric validation exercise was performed using co-incident MERIS RR data and in situ radiometer data from a mooring in the Southern Benguela near Lambert's Bay during the late summer bloom seasons of 2005 and 2006. The data are typified by very high biomass conditions. Sources of error associated with the in situ data are assessed and the magnitudes quantified. The satellite data is examined with particular reference to uncertainty derived from the atmospheric correction processes, which perform unreliably in many of the matchup instances. Results show that the accuracy of the atmospheric correction does not appear to be related to the in-water constituents and is more likely due to atmospheric variability or aerosol features that are not addressed in the models employed by the correction processes. It is also shown that while the radiometric data display a consistent bias in the red region of the spectrum, good correlation with the satellite measurements is observed here under high biomass conditions, underlining the importance of the red wavebands for coastal remote sensing. Recommendations towards the development of a comprehensive regional validation strategy include the establishment of low-cost measurement protocols for high biomass conditions, as well as further investigations into regional atmospheric variability to improve confidence in the atmospheric correction procedures."]},{"key":"dc:title","label":"Title","values":["Radiometric validation of multi-spectral ocean colour satellite data in high biomass Southern Benguela waters"]}]}],"canonical_facts":{"dc:contributor.advisor":["Bernard, Stewart","Shillington, Frank"],"dc:creator":["Robertson, Elisabeth"],"dc:date.accessioned":["2014-10-31T18:06:49Z"],"dc:date.available":["2014-10-31T18:06:49Z"],"dc:date.issued":["2009"],"dc:description":["Includes bibliographical references (leaves 106-117)."],"dc:description.abstract":["This study forms the first step towards a comprehensive ocean colour satellite validation strategy for the Southern Benguela region, and underlines the value of a statistical radiometric validation as a prerequisite to any geophysical validation exercise. A radiometric validation exercise was performed using co-incident MERIS RR data and in situ radiometer data from a mooring in the Southern Benguela near Lambert's Bay during the late summer bloom seasons of 2005 and 2006. The data are typified by very high biomass conditions. Sources of error associated with the in situ data are assessed and the magnitudes quantified. The satellite data is examined with particular reference to uncertainty derived from the atmospheric correction processes, which perform unreliably in many of the matchup instances. Results show that the accuracy of the atmospheric correction does not appear to be related to the in-water constituents and is more likely due to atmospheric variability or aerosol features that are not addressed in the models employed by the correction processes. It is also shown that while the radiometric data display a consistent bias in the red region of the spectrum, good correlation with the satellite measurements is observed here under high biomass conditions, underlining the importance of the red wavebands for coastal remote sensing. Recommendations towards the development of a comprehensive regional validation strategy include the establishment of low-cost measurement protocols for high biomass conditions, as well as further investigations into regional atmospheric variability to improve confidence in the atmospheric correction procedures."],"dc:identifier.uri":["http://hdl.handle.net/11427/9023"],"dc:language.iso":["eng"],"dc:publisher.department":["Department of Oceanography"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["Radiometric validation of multi-spectral ocean colour satellite data in high biomass Southern Benguela waters"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:22:42Z"}