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Using Geometrical, Textural, and Contextual Information of Land Parcels for Classification of Detailed Urban Land Use

Overview of attention for article published in Annals of the Association of American Geographers, January 2009
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
57 Dimensions

Readers on

mendeley
55 Mendeley
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Title
Using Geometrical, Textural, and Contextual Information of Land Parcels for Classification of Detailed Urban Land Use
Published in
Annals of the Association of American Geographers, January 2009
DOI 10.1080/00045600802459028
Authors

Shuo-Sheng Wu, Xiaomin Qiu, E. Lynn Usery, Le Wang

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Argentina 1 2%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 25%
Student > Ph. D. Student 13 24%
Lecturer 4 7%
Student > Master 4 7%
Student > Bachelor 3 5%
Other 7 13%
Unknown 10 18%
Readers by discipline Count As %
Environmental Science 13 24%
Earth and Planetary Sciences 12 22%
Agricultural and Biological Sciences 4 7%
Social Sciences 4 7%
Engineering 4 7%
Other 7 13%
Unknown 11 20%

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 26 February 2020.
All research outputs
#5,494,714
of 17,060,012 outputs
Outputs from Annals of the Association of American Geographers
#234
of 711 outputs
Outputs of similar age
#138,360
of 396,526 outputs
Outputs of similar age from Annals of the Association of American Geographers
#1
of 1 outputs
Altmetric has tracked 17,060,012 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 711 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one is in the 28th percentile – i.e., 28% 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 396,526 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 60% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them