1 January 2011 Detecting patterns and changes in a complex benthic environment of the Baltic Sea
Ele Vahtmae, Tiit Kutser, Jonne Kotta, Merli Parnoja
Author Affiliations +
Abstract
Today, the knowledge on the distribution of marine habitats is very fragmented and temporal changes in such patterns are even less known. In this study we assessed spatial variability and temporal dynamics of benthic habitat types in a relatively turbid northeastern Baltic Sea coastal environment using the space-borne multispectral sensor QuickBird. Seven broad habitat classes were defined for the study area representing the most typical habitats of the coastal environment. The studied classes were bare sand, the brown alga Fucus vesiculosus, hard bottom with ephemeral algae, higher-order plants and/or charophytes on soft bright bottom, dense higher-order plant habitats, and drifting algal mats and deep water (>3 m). Two QuickBird images acquired over a 3 year interval (2005 to 2008) of Western-Estonian archipelago were processed and change detection analysis applied. Although there was a relatively large scatter in reflectance variability within each habitat type, the analyses allowed a clear differentiation of most habitat types. Exceptions were the lack of statistical differences among deep water, drifting algae, and dense higher-order plant communities, as well as among low density higher-order plant and algal communities. Major changes in the spatial patterns of benthic habitats occurred in hydrodynamically active areas. Differences in water properties caused some confusion in classification and therefore resulted in inaccuracies in maps of change. Thus, the used broad habitat classes represent the limit of the method and the multispectral sensors do not allow finer elements of habitats to be captured.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Ele Vahtmae, Tiit Kutser, Jonne Kotta, and Merli Parnoja "Detecting patterns and changes in a complex benthic environment of the Baltic Sea," Journal of Applied Remote Sensing 5(1), 053559 (1 January 2011). https://doi.org/10.1117/1.3653271
Published: 1 January 2011
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Cited by 15 scholarly publications.
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KEYWORDS
Water

Remote sensing

Environmental sensing

Image classification

Reflectivity

Ocean optics

Sensors

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