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Reconstructing long-term global satellite-based soil moisture data using deep learning method

Overview of attention for article published in Frontiers in Earth Science, February 2023
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1 X user

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10 Mendeley
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Title
Reconstructing long-term global satellite-based soil moisture data using deep learning method
Published in
Frontiers in Earth Science, February 2023
DOI 10.3389/feart.2023.1130853
Authors

Yifan Hu, Guojie Wang, Xikun Wei, Feihong Zhou, Giri Kattel, Solomon Obiri Yeboah Amankwah, Daniel Fiifi Tawia Hagan, Zheng Duan

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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 10%
Professor > Associate Professor 1 10%
Student > Postgraduate 1 10%
Student > Master 1 10%
Unknown 6 60%
Readers by discipline Count As %
Environmental Science 3 30%
Earth and Planetary Sciences 1 10%
Unknown 6 60%
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 04 March 2023.
All research outputs
#20,867,287
of 23,485,204 outputs
Outputs from Frontiers in Earth Science
#3,217
of 5,017 outputs
Outputs of similar age
#330,540
of 420,194 outputs
Outputs of similar age from Frontiers in Earth Science
#228
of 540 outputs
Altmetric has tracked 23,485,204 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,017 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% 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 420,194 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 540 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.