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Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data

Overview of attention for article published in Remote Sensing of Environment, September 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
24 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
69 Mendeley
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Title
Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data
Published in
Remote Sensing of Environment, September 2022
DOI 10.1016/j.rse.2022.113089
Authors

Carl J. Legleiter, Tyler V. King, Kurt D. Carpenter, Natalie C. Hall, Adam C. Mumford, Terry Slonecker, Jennifer L. Graham, Victoria G. Stengel, Nancy Simon, Barry H. Rosen

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 22%
Student > Ph. D. Student 11 16%
Unspecified 4 6%
Student > Bachelor 3 4%
Student > Doctoral Student 2 3%
Other 9 13%
Unknown 25 36%
Readers by discipline Count As %
Environmental Science 10 14%
Earth and Planetary Sciences 8 12%
Agricultural and Biological Sciences 7 10%
Engineering 4 6%
Unspecified 4 6%
Other 7 10%
Unknown 29 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 03 August 2022.
All research outputs
#2,184,395
of 25,392,582 outputs
Outputs from Remote Sensing of Environment
#493
of 3,704 outputs
Outputs of similar age
#46,366
of 429,605 outputs
Outputs of similar age from Remote Sensing of Environment
#12
of 74 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,704 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has done well, scoring higher than 86% of its peers.
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 429,605 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.