Geomagnetic Survey Interpolation with the Machine Learning Approach

This paper portrays the method of UAV magnetometry survey data interpolation. The method accommodates the fact that this kind of data has a spatial distribution of the samples along a series of straight lines (similar to maritime tacks), which is a prominent characteristic of many kinds of UAV surve...

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Bibliographic Details
Main Authors: Aleshin Igor, Kholodkov Kirill I., Malygin Ivan, Shevchuk Roman, Sidorov Roman
Format: Article
Language:English
Published: Russian Academy of Sciences, The Geophysical Center 2022-12-01
Series:Russian Journal of Earth Sciences
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Online Access:http://doi.org/10.2205/2022ES000818
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Summary:This paper portrays the method of UAV magnetometry survey data interpolation. The method accommodates the fact that this kind of data has a spatial distribution of the samples along a series of straight lines (similar to maritime tacks), which is a prominent characteristic of many kinds of UAV surveys. The interpolation relies on the very basic nearest neighbourss algorithm, although augmented with a Machine Learning approach. Such an approach enables the error of less than 5 percent by intelligently adjusting the nearest neighbours algorithm parameters. The method was pilot tested on geomagnetic data with Borok Geomagnetic Observatory UAV aeromagnetic survey data.
ISSN:1681-1208