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Machine Learning Techniques for Modelling Short Term Land-Use Change

Overview of attention for article published in ISPRS International Journal of Geo-Information, November 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
12 X users

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
107 Mendeley
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Title
Machine Learning Techniques for Modelling Short Term Land-Use Change
Published in
ISPRS International Journal of Geo-Information, November 2017
DOI 10.3390/ijgi6120387
Authors

Mileva Samardžić-Petrović, Miloš Kovačević, Branislav Bajat, Suzana Dragićević

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users 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 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 107 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 19%
Student > Ph. D. Student 18 17%
Researcher 14 13%
Student > Doctoral Student 4 4%
Lecturer 4 4%
Other 15 14%
Unknown 32 30%
Readers by discipline Count As %
Environmental Science 18 17%
Earth and Planetary Sciences 14 13%
Engineering 13 12%
Computer Science 10 9%
Social Sciences 4 4%
Other 6 6%
Unknown 42 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 29 January 2018.
All research outputs
#6,744,067
of 26,146,017 outputs
Outputs from ISPRS International Journal of Geo-Information
#285
of 2,455 outputs
Outputs of similar age
#118,376
of 451,633 outputs
Outputs of similar age from ISPRS International Journal of Geo-Information
#8
of 45 outputs
Altmetric has tracked 26,146,017 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,455 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 88% 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 451,633 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 73% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.