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Review Article

The application of remote sensing to seagrass ecosystems: an overview and future research prospects

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Pages 61-114 | Received 04 Aug 2014, Accepted 09 Oct 2014, Published online: 13 Dec 2014
 

Abstract

This review evaluates various methods employed to produce seagrass habitat maps using optical and acoustic remote-sensing (RS) techniques coupled with in situ sampling to highlight recent advances and to define areas where potential future research should be focused in the application of RS technologies. A critical review of 195 studies revealed that, in the past four decades, advances in the application of RS methods, notably using Landsat imagery, are identified for seagrass detection, assessment of areal coverage, distribution and abundance mapping, and the detection of extent and biomass changes, as illustrated in peer-reviewed literature. Rapid technological and methodological advances have occurred in the acquisition and interpretation of optical and acoustic data for the mapping of seagrass habitats. The methods have been tested to segment, classify, and combine RS data with biological field or ground truth sample data. There is no single technology or approach that is suitable for and capable of measuring all seagrass parameters (presence/absence, cover, species, and biomass) and assessing change. Integration of field, imagery, and mapping approaches is therefore required. Further research is required for continued improvements in understanding of theoretical and methodological aspects of seagrass RS.

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Erratum

Acknowledgements

The authors would like to thank the editor (Tim Warner) and two anonymous reviewers, whose constructive comments and inputs significantly improved the article. This research was also the result of a collaboration with the Asian Core programme of the Japan Society for the Promotion of Science (JSPS) and Establishment of Research and Education Network on Coastal Marine Science in South East Asia.

Additional information

Funding

This work was supported by the ScienceFund [project code 04-01-04-SF1171] from the Ministry of Science, Technology and Innovation (MOSTI), Malaysia.

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