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Improving the synoptic mapping of coral reef geomorphology using object-based image analysis
Journal article   Peer reviewed

Improving the synoptic mapping of coral reef geomorphology using object-based image analysis

Javier X Leon and C D Woodroffe
International Journal of Geographical Information Science, Vol.25(6), pp.949-969
2011
url
https://doi.org/10.1080/13658816.2010.513980View
Published Version

Abstract

OBIA Torres Strait neural networks classification Landsat ETM+
Monitoring coral reefs is of great importance for environmental management of these ecosystems. The use of remote sensing and geographical information systems enables rapid and effective mapping of the geomorphology of reefs that can be used as a basis for biodiversity and habitat assessments. However, pixel-based approaches have not been appropriate for detailed mapping of such complex systems. An object-based image analysis (OBIA) approach was used in this study to map intra-reef geomorphology of coral reefs across the Torres Strait region using Landsat ETM+ imagery. By combining image analysis techniques and a non-parametric neural network classifier and incorporating additional spatial information such as context, shape and texture, the accuracy of the segmentation and classification was improved considerably. A large-scale synoptic map of 10 geomorphological classes was produced for Torres Strait with an overall accuracy of 75%. The OBIA approach employed in this research has enabled the geomorphology of reef platforms to be mapped for the first time at such accuracy and descriptive resolution. © 2011 Taylor & Francis.

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Web Of Science research areas
Computer Science, Information Systems
Geography
Geography, Physical
Information Science & Library Science

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#13 Climate Action
#14 Life Below Water

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