↓ Skip to main content

Remote Sensing of Seagrass Leaf Area Index and Species: The Capability of a Model Inversion Method Assessed by Sensitivity Analysis and Hyperspectral Data of Florida Bay

Overview of attention for article published in Frontiers in Marine Science, November 2017
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
9 X users

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
75 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Remote Sensing of Seagrass Leaf Area Index and Species: The Capability of a Model Inversion Method Assessed by Sensitivity Analysis and Hyperspectral Data of Florida Bay
Published in
Frontiers in Marine Science, November 2017
DOI 10.3389/fmars.2017.00362
Authors

John D. Hedley, Brandon J. Russell, Kaylan Randolph, Miguel Á. Pérez-Castro, Román M. Vásquez-Elizondo, Susana Enríquez, Heidi M. Dierssen

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 23%
Researcher 11 15%
Student > Doctoral Student 7 9%
Other 5 7%
Student > Master 4 5%
Other 10 13%
Unknown 21 28%
Readers by discipline Count As %
Environmental Science 22 29%
Earth and Planetary Sciences 13 17%
Agricultural and Biological Sciences 4 5%
Unspecified 2 3%
Business, Management and Accounting 1 1%
Other 3 4%
Unknown 30 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 17 December 2017.
All research outputs
#6,353,282
of 23,008,860 outputs
Outputs from Frontiers in Marine Science
#3,396
of 8,525 outputs
Outputs of similar age
#94,195
of 294,546 outputs
Outputs of similar age from Frontiers in Marine Science
#62
of 111 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 8,525 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 59% 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 294,546 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.