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A novel method for cliff vegetation estimation based on the unmanned aerial vehicle 3D modeling

Overview of attention for article published in Frontiers in Plant Science, September 2022
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1 X user

Citations

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5 Mendeley
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Title
A novel method for cliff vegetation estimation based on the unmanned aerial vehicle 3D modeling
Published in
Frontiers in Plant Science, September 2022
DOI 10.3389/fpls.2022.1006795
Pubmed ID
Authors

Minghui Li, Enping Yan, Hui Zhou, Jiaxing Zhu, Jiawei Jiang, Dengkui Mo

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 40%
Student > Master 2 40%
Researcher 1 20%
Readers by discipline Count As %
Unspecified 3 60%
Earth and Planetary Sciences 1 20%
Engineering 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 13 October 2022.
All research outputs
#18,967,733
of 23,515,383 outputs
Outputs from Frontiers in Plant Science
#14,712
of 21,530 outputs
Outputs of similar age
#303,218
of 436,276 outputs
Outputs of similar age from Frontiers in Plant Science
#845
of 1,426 outputs
Altmetric has tracked 23,515,383 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,530 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 436,276 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,426 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.