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Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model

Overview of attention for article published in Remote Sensing of Environment, June 2022
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
90 X users

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
100 Mendeley
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Title
Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model
Published in
Remote Sensing of Environment, June 2022
DOI 10.1016/j.rse.2022.113011
Authors

Gabriel B. Senay, MacKenzie Friedrichs, Charles Morton, Gabriel E.L. Parrish, Matthew Schauer, Kul Khand, Stefanie Kagone, Olena Boiko, Justin Huntington

X Demographics

X Demographics

The data shown below were collected from the profiles of 90 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 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 18%
Researcher 14 14%
Student > Master 12 12%
Lecturer 4 4%
Student > Bachelor 2 2%
Other 6 6%
Unknown 44 44%
Readers by discipline Count As %
Environmental Science 15 15%
Agricultural and Biological Sciences 12 12%
Earth and Planetary Sciences 10 10%
Engineering 6 6%
Economics, Econometrics and Finance 1 1%
Other 3 3%
Unknown 53 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 60. 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 27 May 2022.
All research outputs
#751,202
of 26,253,210 outputs
Outputs from Remote Sensing of Environment
#112
of 3,845 outputs
Outputs of similar age
#18,353
of 451,271 outputs
Outputs of similar age from Remote Sensing of Environment
#3
of 38 outputs
Altmetric has tracked 26,253,210 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,845 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has done particularly well, scoring higher than 97% 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 451,271 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.