Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Inorganic Suspended Matter as an indicator of terrestrial influence in Baltic Sea coastal areas - algorithm development, validation and ecological relevance
Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
(English)Manuscript (preprint) (Other academic)
National Category
Biological Sciences
Research subject
Marine Ecology
Identifiers
URN: urn:nbn:se:su:diva-170587OAI: oai:DiVA.org:su-170587DiVA, id: diva2:1341923
Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-08-12Bibliographically approved
In thesis
1. Baltic Sea from Space: The use of ocean colour data to improve our understanding of ecological drivers across the Baltic Sea basin – algorithm development, validation and ecological applications
Open this publication in new window or tab >>Baltic Sea from Space: The use of ocean colour data to improve our understanding of ecological drivers across the Baltic Sea basin – algorithm development, validation and ecological applications
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Coastal areas are the most densely populated areas in the world and thus are under immense anthropogenic pressure. To ensure their function and ecological role, coastal areas require continuous monitoring and management. The rapidly emerging field of satellite remote sensing provides a unique opportunity to monitor both land and oceans from Space. This thesis explores recent developments in ocean colour remote sensing, tests several image processing algorithms, evaluates and maps water quality indicators – both on local and Baltic Sea-wide scale – as well as provides essential monitoring data to complement already existing ship-based monitoring and modelling techniques. The overall aim of the thesis is to broaden our understanding and applicability of ocean colour remote sensing for improved modelling and management of the Baltic Sea and its coastal areas.

The thesis deals with four independent research topics. In paper I the spatial distribution of Total Suspended Matter (TSM) during the summer season is evaluated using the European Space Agency’s (ESA) MEdium Resolution Imaging Spectrometer (MERIS). The TSM distribution and concentration is retrieved quantitatively from MERIS data for the HELCOM-defined Baltic Sea sub-basins for the summer seasons 2009, 2010, 2011, and summarized in a 3-year summer composite image. Manuscript II deals with the correspondence between satellite, in situ and modelled data in Bråviken bay, NW Baltic proper, which is optically dominated by Coloured Dissolved Organic Matter (CDOM). Chlorophyll-a (CHL-a) and Secchi depth data are analyzed along a horizontal transects reaching from the inner coastal bay out into the open sea. The study addresses the scarcity of in situ monitoring data in comparison to satellite and modelled data. Further, an empirical relationship is established between modelled total nitrogen and CHL-a derived from satellite, potentially allowing to infer information on the distribution of total nitrogen from satellite data. Paper III evaluates the performance of MERIS’s successor – the Ocean and Land Colour Instrument (OLCI) launched on board Sentinel-3A (S3A) satellite. The water quality products derived from S3A OLCI using the Case-2 Regional CoastColour Processor are evaluated via several dedicated validation campaigns (2016-2018) in the NW Baltic proper. In manuscript IV, the in-water relationship between particle scatter at 440 nm and Inorganic Suspended Particulate Matter (ISPM) is used to develop a novel algorithm to derive ISPM from satellite-derived scatter. This algorithm was applied to OLCI data and tested on an independent dataset. The algorithm allows to map the distribution of ISPM across the Baltic Sea basin and to assess the influence of coastal processes.

The key outcome of this thesis are reliable water-quality products generated on a Baltic Sea-wide scale, using state-of-the-art Ocean Colour data. Specifically, the thesis highlights the benefits of using remote sensing to improve our understanding of coastal and dynamical processes, as well as Baltic Sea ecology on a wider scale, which simply is not possible by any other scientific means. 

Place, publisher, year, edition, pages
Stockholm: Department of Ecology, Environment and Plant Sciences, Stockholm University, 2019
Keywords
Ocean Colour, MERIS, OLCI, water quality, marine ecology, coastal areas, Baltic Sea
National Category
Ecology
Research subject
Marine Ecology
Identifiers
urn:nbn:se:su:diva-170588 (URN)978-91-7797-793-3 (ISBN)978-91-7797-794-0 (ISBN)
Public defence
2019-09-27, sal P216, NPQ-huset, Svante Arrhenius väg 20 A, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
Swedish National Space Board, Dnr. 147/12The European Space Agency (ESA), ESA/ESRIN project 12352/08/I-OLNordForsk, Project 80106
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.

Available from: 2019-09-04 Created: 2019-08-12 Last updated: 2019-08-27Bibliographically approved

Open Access in DiVA

No full text in DiVA

Search in DiVA

By author/editor
Kratzer, SusanneKyryliuk, Dmytro
By organisation
Department of Ecology, Environment and Plant Sciences
Biological Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 15 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf