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Remote estimation of rapeseed yield with unmanned aerial vehicle (UAV) imaging and spectral mixture analysis

Overview of attention for article published in Plant Methods, August 2018
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3 tweeters
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2 Facebook pages

Citations

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26 Dimensions

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50 Mendeley
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Title
Remote estimation of rapeseed yield with unmanned aerial vehicle (UAV) imaging and spectral mixture analysis
Published in
Plant Methods, August 2018
DOI 10.1186/s13007-018-0338-z
Pubmed ID
Authors

Yan Gong, Bo Duan, Shenghui Fang, Renshan Zhu, Xianting Wu, Yi Ma, Yi Peng

Abstract

The accurate quantification of yield in rapeseed is important for evaluating the supply of vegetable oil, especially at regional scales. This study developed an approach to estimate rapeseed yield with remotely sensed canopy spectra and abundance data by spectral mixture analysis. A six-band image of the studied rapeseed plots was obtained by an unmanned aerial vehicle (UAV) system during the rapeseed flowering stage. Several widely used vegetation indices (VIs) were calculated from canopy reflectance derived from the UAV image. And the plot-level abundance of flower, leaf and soil, indicating the fraction of different components within the plot, was retrieved based on spectral mixture analysis on the six-band image and endmember spectra collected in situ for different components. The results showed that for all tested indices VI multiplied by leaf-related abundance closely related to rapeseed yield. The product of Normalized Difference Vegetation Index and short-stalk-leaf abundance was the most accurate for estimating yield in rapeseed under different nitrogen treatments with the estimation errors below 13%. This study gives an important indication that spectral mixture analysis needs to be considered when estimating yield by remotely sensed VI, especially for the image containing obviously spectral different components or for crops which have conspicuous flowers or fruits with significantly different spectra from their leave.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Master 7 14%
Student > Ph. D. Student 5 10%
Student > Bachelor 4 8%
Student > Postgraduate 3 6%
Other 8 16%
Unknown 13 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 36%
Earth and Planetary Sciences 4 8%
Computer Science 4 8%
Engineering 3 6%
Environmental Science 2 4%
Other 5 10%
Unknown 14 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 20 September 2018.
All research outputs
#7,802,619
of 13,533,246 outputs
Outputs from Plant Methods
#349
of 590 outputs
Outputs of similar age
#138,343
of 266,538 outputs
Outputs of similar age from Plant Methods
#2
of 3 outputs
Altmetric has tracked 13,533,246 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 590 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 36th percentile – i.e., 36% 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 266,538 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.