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Snow Depth Retrieval With an Autonomous UAV-Mounted Software-Defined Radar

Overview of attention for article published in IEEE Transactions on Geoscience and Remote Sensing, January 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
5 tweeters

Readers on

mendeley
7 Mendeley
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Title
Snow Depth Retrieval With an Autonomous UAV-Mounted Software-Defined Radar
Published in
IEEE Transactions on Geoscience and Remote Sensing, January 2022
DOI 10.1109/tgrs.2021.3117509
Authors

Samuel Prager, Graham Sexstone, Daniel McGrath, John Fulton, Mahta Moghaddam

Twitter Demographics

The data shown below were collected from the profiles of 5 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Professor 1 14%
Researcher 1 14%
Student > Ph. D. Student 1 14%
Unknown 2 29%
Readers by discipline Count As %
Earth and Planetary Sciences 3 43%
Engineering 2 29%
Unknown 2 29%

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 16 November 2021.
All research outputs
#5,836,876
of 21,225,914 outputs
Outputs from IEEE Transactions on Geoscience and Remote Sensing
#529
of 2,419 outputs
Outputs of similar age
#137,718
of 421,953 outputs
Outputs of similar age from IEEE Transactions on Geoscience and Remote Sensing
#5
of 18 outputs
Altmetric has tracked 21,225,914 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,419 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 78% 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 421,953 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 67% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.