基于机器学习的地磁测量插值方法
Geomagnetic Survey Interpolation with the Machine Learning Approach
摘要：
介绍了无人机磁力测量数据内插的方法。该方法适应了这类数据具有样本沿一系列直线（类似于海上航迹）的空间发布的事实，这是许多无人机测量的突出特点。插值依赖于非常基本的最近邻算法，尽管使用了机器学习方法。这种方法通过智能地调整最近邻算法参数使误差小于5%。利用Borok地磁台无人机航磁测量数据对该方法进行了初步测试。
英文摘要：
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 Neighbours algorithm, although augmented with a Machine Learning approach. Such an approach enables the error of less than 5 percent by intelligently adjusting the Nearest Neighbour algorithm parameters. The method was pilot tested on geomagnetic data with Borok Geomagnetic Observatory UAV aeromagnetic survey data.
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