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Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest

Overview of attention for article published in Remote Sensing, June 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

policy
1 policy source

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest
Published in
Remote Sensing, June 2015
DOI 10.3390/rs70607298
Authors

Dominik Jaskierniak, George Kuczera, Richard Benyon, Luke Wallace

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Student > Master 8 24%
Researcher 4 12%
Student > Doctoral Student 2 6%
Other 2 6%
Other 5 15%
Unknown 4 12%
Readers by discipline Count As %
Environmental Science 10 29%
Earth and Planetary Sciences 6 18%
Engineering 5 15%
Agricultural and Biological Sciences 4 12%
Nursing and Health Professions 1 3%
Other 0 0%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 January 2017.
All research outputs
#7,482,726
of 22,873,031 outputs
Outputs from Remote Sensing
#3,231
of 11,348 outputs
Outputs of similar age
#90,858
of 267,088 outputs
Outputs of similar age from Remote Sensing
#27
of 108 outputs
Altmetric has tracked 22,873,031 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,348 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 69% 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 267,088 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 56% of its contemporaries.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.