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Fluorescence-Based Classification of Caribbean Coral Reef Organisms and Substrates

Overview of attention for article published in PLoS ONE, January 2014
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Fluorescence-Based Classification of Caribbean Coral Reef Organisms and Substrates
Published in
PLoS ONE, January 2014
DOI 10.1371/journal.pone.0084570
Pubmed ID

David G. Zawada, Charles H. Mazel


A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: 'optimally-picked' and 'evenly-spaced.' The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled water-column attenuation. The classification results from both tests indicate that a high degree of separability among the 15 fluorescent-spectra functional groups is possible using only a modest number of spectral bands.

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 3%
South Africa 1 3%
Unknown 29 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Student > Master 4 13%
Student > Doctoral Student 4 13%
Researcher 3 10%
Student > Bachelor 3 10%
Other 7 23%
Unknown 3 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 42%
Environmental Science 4 13%
Computer Science 3 10%
Engineering 2 6%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 5 16%
Unknown 3 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 October 2014.
All research outputs
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Outputs from PLoS ONE
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Outputs of similar age
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Outputs of similar age from PLoS ONE
of 3,099 outputs
Altmetric has tracked 12,091,627 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 133,030 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 227,122 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,099 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.