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Aerodynamic Roughness Length Estimation with Lidar and Imaging Spectroscopy in a Shrub-Dominated Dryland

Overview of attention for article published in Photogrammetric Engineering & Remote Sensing, June 2017
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
14 Mendeley
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Title
Aerodynamic Roughness Length Estimation with Lidar and Imaging Spectroscopy in a Shrub-Dominated Dryland
Published in
Photogrammetric Engineering & Remote Sensing, June 2017
DOI 10.14358/pers.83.6.415
Authors

Aihua Li, Wenguang Zhao, Jessica J. Mitchell, Nancy F. Glenn, Matthew J. Germino, Joel B. Sankey, Richard G. Allen

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 21%
Researcher 3 21%
Student > Ph. D. Student 2 14%
Professor 2 14%
Unknown 4 29%
Readers by discipline Count As %
Earth and Planetary Sciences 5 36%
Agricultural and Biological Sciences 1 7%
Mathematics 1 7%
Engineering 1 7%
Unknown 6 43%

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 July 2017.
All research outputs
#7,143,839
of 11,465,445 outputs
Outputs from Photogrammetric Engineering & Remote Sensing
#81
of 94 outputs
Outputs of similar age
#148,016
of 258,264 outputs
Outputs of similar age from Photogrammetric Engineering & Remote Sensing
#1
of 1 outputs
Altmetric has tracked 11,465,445 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 94 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 10th percentile – i.e., 10% 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 258,264 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them