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Data fusion for mapping coral reef geomorphic zones: Possibilities and limitations

Conference Paper


Abstract


  • Mapping the geomorphology of coral reefs provides key information to scientists and managers about the distribution, extent and

    structure of reef landforms. Geomorphological zones within a reef system are underpinned by geological and environmental

    gradients in physical and biological processes, usually resulting in well-defined and clearly recognisable landforms. Mapping of such

    zones has been traditionally undertaken by visual interpretation of remotely sensed imagery, with mapping performance constrained

    by the operator‟s contextual interpretation and/or imagery characteristics. However, mapping criteria are subjective and often not

    transferable to other sites. This study explores a semi-automatic, GEO-Object-Based Image Analysis (GEOBIA) approach to

    mapping intra-reef geomorphological zones based on fusing high-resolution satellite imagery and seamless elevation data. The

    method is applied to Quickbird and Worldview2 imagery of two coral reefs in Australia: Bet Reef, an intertidal lagoonal reef

    platform in the central Torres Strait; and Lizard Island, a fringing reef in northern Great Barrier Reef (GBR). Combining optical and

    bathymetric information considerably improved classification results from ~ 80% to ~ 90% overall accuracy. Rule sets developed

    based on this data fusion approach have the potential to be transferable between different reef types across geographic settings.

UOW Authors


  •   Leon, Javier X. (external author)
  •   Phinn, Stuart R. (external author)
  •   Woodroffe, Colin
  •   Hamylton, Sarah
  •   Roelfsema, Chris M. (external author)
  •   Saunders, Megan L. (external author)

Publication Date


  • 2012

Citation


  • Leon, J., Phinn, S. R., Woodroffe, C. D., Hamylton, S., Roelfsema, C. & Saunders, M. (2012). Data fusion for mapping coral reef geomorphic zones: Possibilities and limitations. 4th International Conference on Geographic Object-Based Image Analysis (GEOBIA 2012) (pp. 1-6).

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Abstract


  • Mapping the geomorphology of coral reefs provides key information to scientists and managers about the distribution, extent and

    structure of reef landforms. Geomorphological zones within a reef system are underpinned by geological and environmental

    gradients in physical and biological processes, usually resulting in well-defined and clearly recognisable landforms. Mapping of such

    zones has been traditionally undertaken by visual interpretation of remotely sensed imagery, with mapping performance constrained

    by the operator‟s contextual interpretation and/or imagery characteristics. However, mapping criteria are subjective and often not

    transferable to other sites. This study explores a semi-automatic, GEO-Object-Based Image Analysis (GEOBIA) approach to

    mapping intra-reef geomorphological zones based on fusing high-resolution satellite imagery and seamless elevation data. The

    method is applied to Quickbird and Worldview2 imagery of two coral reefs in Australia: Bet Reef, an intertidal lagoonal reef

    platform in the central Torres Strait; and Lizard Island, a fringing reef in northern Great Barrier Reef (GBR). Combining optical and

    bathymetric information considerably improved classification results from ~ 80% to ~ 90% overall accuracy. Rule sets developed

    based on this data fusion approach have the potential to be transferable between different reef types across geographic settings.

UOW Authors


  •   Leon, Javier X. (external author)
  •   Phinn, Stuart R. (external author)
  •   Woodroffe, Colin
  •   Hamylton, Sarah
  •   Roelfsema, Chris M. (external author)
  •   Saunders, Megan L. (external author)

Publication Date


  • 2012

Citation


  • Leon, J., Phinn, S. R., Woodroffe, C. D., Hamylton, S., Roelfsema, C. & Saunders, M. (2012). Data fusion for mapping coral reef geomorphic zones: Possibilities and limitations. 4th International Conference on Geographic Object-Based Image Analysis (GEOBIA 2012) (pp. 1-6).

Start Page


  • 1

End Page


  • 6