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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

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
8 tweeters

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
80 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 Glenn, Lucas Spaete, Douglas Shinneman, David Pilliod, Robert Arkle, Susan McIlroy

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 24%
Student > Ph. D. Student 17 21%
Researcher 15 19%
Student > Doctoral Student 9 11%
Student > Postgraduate 6 8%
Other 8 10%
Unknown 6 8%
Readers by discipline Count As %
Earth and Planetary Sciences 21 26%
Agricultural and Biological Sciences 19 24%
Environmental Science 15 19%
Computer Science 3 4%
Engineering 2 3%
Other 3 4%
Unknown 17 21%

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 06 November 2019.
All research outputs
#4,253,595
of 16,156,125 outputs
Outputs from Remote Sensing
#1,337
of 6,957 outputs
Outputs of similar age
#81,225
of 274,242 outputs
Outputs of similar age from Remote Sensing
#32
of 217 outputs
Altmetric has tracked 16,156,125 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 6,957 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 80% 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 274,242 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 70% of its contemporaries.
We're also able to compare this research output to 217 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.