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Lidar Aboveground Vegetation Biomass Estimates in Shrublands: Prediction, Uncertainties and Application to Coarser Scales

Overview of attention for article published in Remote Sensing, August 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
6 X users

Citations

dimensions_citation
57 Dimensions

Readers on

mendeley
127 Mendeley
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Title
Lidar Aboveground Vegetation Biomass Estimates in Shrublands: Prediction, Uncertainties and Application to Coarser Scales
Published in
Remote Sensing, August 2017
DOI 10.3390/rs9090903
Authors

Aihua Li, Shital Dhakal, Nancy F. Glenn, Lucas P. Spaete, Douglas J. Shinneman, David S. Pilliod, Robert S. Arkle, Susan K. McIlroy

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 127 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 20%
Student > Master 20 16%
Researcher 19 15%
Student > Doctoral Student 13 10%
Other 7 6%
Other 18 14%
Unknown 25 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 20%
Earth and Planetary Sciences 25 20%
Environmental Science 23 18%
Engineering 3 2%
Computer Science 3 2%
Other 5 4%
Unknown 42 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 06 November 2019.
All research outputs
#8,174,832
of 25,376,589 outputs
Outputs from Remote Sensing
#3,492
of 13,286 outputs
Outputs of similar age
#110,038
of 299,995 outputs
Outputs of similar age from Remote Sensing
#46
of 218 outputs
Altmetric has tracked 25,376,589 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 13,286 research outputs from this source. They receive a mean Attention Score of 4.5. This one has gotten more attention than average, scoring higher than 73% 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 299,995 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 63% of its contemporaries.
We're also able to compare this research output to 218 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.