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Coastal marine eutrophication assessment: a review on data analysis
Kitsiou, D.; Karydis, M. (2011). Coastal marine eutrophication assessment: a review on data analysis. Environ. Int. 37(4): 778-801. https://dx.doi.org/10.1016/j.envint.2011.02.004
In: Environment International. Pergamon: New York. ISSN 0160-4120; e-ISSN 1873-6750, meer
Peer reviewed article  

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Trefwoord
    Marien/Kust
Author keywords
    Statistical methodology; Multicriteria analysis; Spatial analysis; Geostatistics; Mapping; GIS applications

Auteurs  Top 
  • Kitsiou, D., meer
  • Karydis, M.

Abstract
    A wide variety of data analysis techniques have been applied for quantitative assessment of coastal marine eutrophication. Indicators for assessing eutrophication and frequency distributions have been used to develop scales for characterizing oligotrophy and eutrophication. Numerical classification has also contributed to the assessment of eutrophic trends by grouping sampling sites of similar trophic conditions. Applications of eutrophication assessment based on Principal Component Analysis and Multidimensional Scaling have also been carried out. In addition, the rapid development of Geographical Information Systems has provided the framework for applications of spatial methods and mapping techniques on eutrophication studies. Satellite data have also contributed to eutrophication assessment especially at large scale. Multiple criteria analysis methods can integrate eutrophication variables together with socio-economic parameters providing a holistic approach particularly useful to policy makers. As the current concept of eutrophication problems is to be examined as part of a coastal management approach, more complex quantitative procedures are needed to provide a platform useful for implementation of environmental policy. The present work reviews methods of data analysis used for the assessment of coastal marine eutrophication. The difficulties in applying these methods on data collected from the marine environment are discussed as well as the future perspectives of spatial and multiple criteria choice methods.

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