• Chris M. Roelfsema
  • Stuart R. Phinn


Adequate understanding of the validity of information contained in coral reef remote sensing products is required to support research and management decisions. This chapter introduces accuracy measures commonly applied to two types of coral related maps: discrete (e.g., benthic cover type) and continuous (e.g., percent coral cover). A critical review of 80 coral reef remote sensing mapping publications presents the approaches and metrics commonly used to measure accuracy. The literature review shows that few studies report accuracy information at all, and when obtained, ‘overall accuracy’ was the most commonly used accuracy measure. Variations in accuracy levels were not only a result of actual differences in map accuracy, but are likely also due to: spatial complexity of benthic features present in the study area; distribution of the calibration and validation samples relative to each other; and the level of detail measured for each sample. As a result, accuracy measures from different studies should be compared with caution and with due attention to how the measures were derived. This chapter enables scientist and managers to understand, design and interpret validation procedures for image-based maps of coral reef environments.


Coral Reef Great Barrier Reef Accuracy Assessment Error Matrix Coral Reef Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded through ARC Discovery Project—Innovative Coral Reef Mapping, University of Queensland, University of South Pacific, World Bank GEF Coral Reef Target Research—Remote Sensing working group, South Pacific Applied Geoscience Committee, Coral Cay Conservation, and Coral Reef Initiative for the Pacific. Bill Aalbersberg, James Comley and Leon Zann for their support and assistance. The fourteen participants of the map user assessment. Assitance from D. Kleine and the people Navakavu and Dravuni Qoliqoli.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Biophysical Remote Sensing Group, School of Geography, Planning and Environmental ManagementThe University of QueenslandQueenslandAustralia

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