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Repeatability analysis of airborne electromagnetic surveys

Overview of attention for article published in Mathematics-in-Industry Case Studies, September 2016
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Title
Repeatability analysis of airborne electromagnetic surveys
Published in
Mathematics-in-Industry Case Studies, September 2016
DOI 10.1186/s40929-016-0008-1
Pubmed ID
Authors

Avril Hegarty, Gerry Stanley, Eugene Kashdan, Jim Hodgson, Andrew C. Parnell, Hegarty, Avril

Abstract

We provide methods for determining the repeatability of airborne electromagnetic surveys when conducted at different altitudes over a number of repeated flights. Our data arise from the TELLUS project carried out by the Geological Surveys of Ireland and Northern Ireland and we examine the repeatability of the apparent resistivity at different frequencies. After considering a number of issues with the data, we propose two different models from the functional data analysis literature; a Weiner process with random effects, and a penalised spline smoother. Both methods arrive at the same conclusion regarding repeatability of the data; results obtained are more repeatable for flights at lower altitudes. The target altitude for aircraft carrying out airborne electromagnetic surveys should be as low as possible.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Other 1 20%
Lecturer 1 20%
Unspecified 1 20%
Readers by discipline Count As %
Earth and Planetary Sciences 2 40%
Mathematics 2 40%
Unspecified 1 20%

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 15 September 2016.
All research outputs
#4,075,766
of 8,558,835 outputs
Outputs from Mathematics-in-Industry Case Studies
#2
of 2 outputs
Outputs of similar age
#118,766
of 254,247 outputs
Outputs of similar age from Mathematics-in-Industry Case Studies
#2
of 2 outputs
Altmetric has tracked 8,558,835 research outputs across all sources so far. This one has received more attention than most of these and is in the 50th percentile.
So far Altmetric has tracked 2 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one scored the same or higher as 0 of them.
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 254,247 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 50% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.