Edinburgh Research Archive logo

Edinburgh Research Archive

University of Edinburgh homecrest
View Item 
  •   ERA Home
  • Geosciences, School of
  • GeoSciences MSc thesis collection
  • View Item
  •   ERA Home
  • Geosciences, School of
  • GeoSciences MSc thesis collection
  • View Item
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

Improvements in the mapping of shallow marine habitats through predictive spatial modelling

View/Open
pwalker_research_paper.pdf (3.082Mb)
pwalker_technical_report.pdf (6.466Mb)
Date
08//2/05/1
Item status
Restricted Access
Author
Walker, Peter R
Metadata
Show full item record
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.
URI
http://hdl.handle.net/1842/2465
Collections
  • GeoSciences MSc thesis collection

Library & University Collections HomeUniversity of Edinburgh Information Services Home
Privacy & Cookies | Takedown Policy | Accessibility | Contact
Privacy & Cookies
Takedown Policy
Accessibility
Contact
feed RSS Feeds

RSS Feed not available for this page

 

 

All of ERACommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsPublication TypeSponsorSupervisorsThis CollectionBy Issue DateAuthorsTitlesSubjectsPublication TypeSponsorSupervisors
LoginRegister

Library & University Collections HomeUniversity of Edinburgh Information Services Home
Privacy & Cookies | Takedown Policy | Accessibility | Contact
Privacy & Cookies
Takedown Policy
Accessibility
Contact
feed RSS Feeds

RSS Feed not available for this page