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Fine-Resolution Repeat Topographic Surveying of Dryland Landscapes Using UAS-Based Structure-from-Motion Photogrammetry: Assessing Accuracy and Precision against Traditional Ground-Based Erosion…

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

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
7 X users

Citations

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25 Dimensions

Readers on

mendeley
112 Mendeley
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Title
Fine-Resolution Repeat Topographic Surveying of Dryland Landscapes Using UAS-Based Structure-from-Motion Photogrammetry: Assessing Accuracy and Precision against Traditional Ground-Based Erosion Measurements
Published in
Remote Sensing, May 2017
DOI 10.3390/rs9050437
Authors

Jeffrey K. Gillan, Jason W. Karl, Ahmed Elaksher, Michael C. Duniway

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 111 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 23%
Researcher 21 19%
Student > Master 16 14%
Student > Bachelor 11 10%
Student > Doctoral Student 4 4%
Other 14 13%
Unknown 20 18%
Readers by discipline Count As %
Environmental Science 29 26%
Earth and Planetary Sciences 29 26%
Engineering 17 15%
Agricultural and Biological Sciences 7 6%
Computer Science 2 2%
Other 4 4%
Unknown 24 21%
Attention Score in Context

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 21 December 2017.
All research outputs
#6,426,164
of 22,968,808 outputs
Outputs from Remote Sensing
#2,490
of 11,404 outputs
Outputs of similar age
#102,388
of 310,917 outputs
Outputs of similar age from Remote Sensing
#42
of 306 outputs
Altmetric has tracked 22,968,808 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 11,404 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 77% 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 310,917 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 66% of its contemporaries.
We're also able to compare this research output to 306 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.