Improvements in the mapping of shallow marine habitats through predictive spatial modelling
dc.contributor.advisor
Malthus, Tim
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dc.contributor.author
Walker, Peter R.
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dc.date.accessioned
2008-08-20T10:17:55Z
dc.date.available
2008-08-20T10:17:55Z
dc.date.issued
2008-12-05
dc.description.abstract
The UK has an obligation to monitor certain sites around its coastline due to various International environmental designations. Remote sensing is ideal as these areas are often difficult and hazardous to access. Traditionally, classification has been based on the spectral responses of targets, but indistinct spectral signatures between targets often leads to poor classification accuracy.
To improve this, other methods of classification such as predictive spatial modelling (PSM) incorporate ‘knowledge’ of a study area in addition to the target’s spectral information. Well documented natural zonation of shallow marine habitats make them especially suitable for classification using PSM techniques. Using the ERDAS Knowledge Engineer, a series of knowledge-based rules relating to exposure, depth and substrate were tested, combined with QuickBird high spatial resolution remotely sensed data, to improve the classification of a study area in the Sound of Harris, Outer Hebrides, Scotland.
Results show that after preliminary supervised classification based on spectral parameters, the additional rules enabled further subdivision of spectrally similar classes, and the simultaneous classification of both subtidal and intertidal biotopes in one process. This is an improvement on previous attempts which subset and separately classified the subtidal and intertidal areas. While the approach shows potential, considerable biotope confusion still exists, which resulted in a low overall accuracy of just under 40%. The need for further discriminating factors to improve the classification, as well as a more robust knowledge based approach, are highlighted as potential future improvements.
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dc.format.extent
6780910 bytes
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3232709 bytes
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dc.format.mimetype
application/pdf
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dc.format.mimetype
application/pdf
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dc.identifier.uri
http://hdl.handle.net/1842/2465
dc.language.iso
en
dc.subject
Predictive spatial modelling
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dc.subject
Biotope
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dc.subject
Shallow marine
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dc.subject
Classification
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dc.subject
Hebrides
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dc.subject
GIS
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dc.subject
MSc Geographical Information Science
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dc.subject
GIS
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dc.title
Improvements in the mapping of shallow marine habitats through predictive spatial modelling
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Masters
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dc.type.qualificationname
MSc Master of Science
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dcterms.accessRights
RESTRICTED ACCESS
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