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A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Overview of attention for article published in ISPRS Journal of Photogrammetry & Remote Sensing, October 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

policy
1 policy source

Citations

dimensions_citation
150 Dimensions

Readers on

mendeley
414 Mendeley
citeulike
3 CiteULike
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Title
A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform
Published in
ISPRS Journal of Photogrammetry & Remote Sensing, October 2018
DOI 10.1016/j.isprsjprs.2018.07.017
Authors

Pardhasaradhi Teluguntla, Prasad S Thenkabail, Adam Oliphant, Jun Xiong, Murali Krishna Gumma, Russell G. Congalton, Kamini Yadav, Alfredo Huete

Mendeley readers

The data shown below were compiled from readership statistics for 414 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 414 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 75 18%
Student > Ph. D. Student 68 16%
Researcher 64 15%
Student > Bachelor 28 7%
Student > Doctoral Student 23 6%
Other 54 13%
Unknown 102 25%
Readers by discipline Count As %
Environmental Science 76 18%
Earth and Planetary Sciences 61 15%
Engineering 42 10%
Agricultural and Biological Sciences 40 10%
Computer Science 39 9%
Other 32 8%
Unknown 124 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 March 2021.
All research outputs
#6,080,754
of 18,750,173 outputs
Outputs from ISPRS Journal of Photogrammetry & Remote Sensing
#294
of 702 outputs
Outputs of similar age
#112,573
of 286,479 outputs
Outputs of similar age from ISPRS Journal of Photogrammetry & Remote Sensing
#11
of 24 outputs
Altmetric has tracked 18,750,173 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 702 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 34th percentile – i.e., 34% 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 286,479 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 57% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.