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Remote Sens. 2013, 5(5), 2451-2474; doi:10.3390/rs5052451

Classifying the Baltic Sea Shallow Water Habitats Using Image-Based and Spectral Library Methods

Estonian Marine Institute, University of Tartu, Mäealuse 14, 12618 Tallinn, Estonia
Author to whom correspondence should be addressed.
Received: 15 March 2013 / Revised: 30 April 2013 / Accepted: 2 May 2013 / Published: 16 May 2013
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The structure of benthic macrophyte habitats is known to indicate the quality of coastal water. Thus, a large-scale analysis of the spatial patterns of coastal marine habitats enables us to adequately estimate the status of valuable coastal marine habitats, provide better evidence for environmental changes and describe processes that are behind the changes. Knowing the spatial distribution of benthic habitats is also important from the coastal management point of view. A big challenge in remote sensing mapping of benthic habitats is to define appropriate mapping classes that are also meaningful from the ecological point of view. In this study, the benthic habitat classification scheme was defined for the study areas in the relatively turbid north-eastern Baltic Sea coastal environment. Two different classification methods—image-based and the spectral library—method were used for image classification. The image-based classification method can provide benthic habitat maps from coastal areas, but requires extensive field studies. An alternative approach in image classification is to use measured and/or modelled spectral libraries. This method does not require fieldwork at the time of image collection if preliminary information about the potential benthic habitats and their spectral properties, as well as variability in optical water properties exists from earlier studies. A spectral library was generated through radiative transfer model HydroLight computations using measured reflectance spectra from representative benthic substrates and water quality measurements. Our previous results have shown that benthic habitat mapping should be done at high spatial resolution, owing to the small-scale heterogeneity of such habitats in the Estonian coastal waters. In this study, the capability of high spatial resolution hyperspectral airborne a Compact Airborne Spectrographic Imager (CASI) sensor and a high spatial resolution multispectral WorldView-2 satellite sensor were tested for mapping benthic habitats. Initial evaluations of habitat maps indicate that image-based classification provides higher quality benthic maps compared to the spectral library method. View Full-Text
Keywords: Baltic Sea; benthic habitat mapping; CASI; WorldView-2; image processing; spectral library; HydroLight Baltic Sea; benthic habitat mapping; CASI; WorldView-2; image processing; spectral library; HydroLight

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Vahtmäe, E.; Kutser, T. Classifying the Baltic Sea Shallow Water Habitats Using Image-Based and Spectral Library Methods. Remote Sens. 2013, 5, 2451-2474.

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