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Machine learning algorithms for lithological mapping using Sentinel-2 and SRTM DEM in highly vegetated areas

Overview of attention for article published in Frontiers in Ecology and Evolution, October 2023
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
2 X users

Citations

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3 Dimensions

Readers on

mendeley
10 Mendeley
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Title
Machine learning algorithms for lithological mapping using Sentinel-2 and SRTM DEM in highly vegetated areas
Published in
Frontiers in Ecology and Evolution, October 2023
DOI 10.3389/fevo.2023.1250971
Authors

Yansi Chen, Yulong Dong, Yunchen Wang, Feng Zhang, Genyuan Liu, Peiheng Sun

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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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 %
Researcher 3 30%
Unspecified 2 20%
Student > Master 2 20%
Unknown 3 30%
Readers by discipline Count As %
Earth and Planetary Sciences 3 30%
Unspecified 2 20%
Computer Science 1 10%
Engineering 1 10%
Unknown 3 30%
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 18 October 2023.
All research outputs
#19,342,464
of 24,631,014 outputs
Outputs from Frontiers in Ecology and Evolution
#3,260
of 4,988 outputs
Outputs of similar age
#97,632
of 153,083 outputs
Outputs of similar age from Frontiers in Ecology and Evolution
#29
of 102 outputs
Altmetric has tracked 24,631,014 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,988 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one is in the 29th percentile – i.e., 29% 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 153,083 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.