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Approach to adaptive spatial interpolation of geophysical information
A.V. Vorobev 1,2, G.R. Vorobeva 1

1 Geophysical Center of RAS,
119296, Moscow, Russia, Molodezhnaya St. 3;
2 Ufa University of Science and Technology, Ufa, Russia,
K. Marx St. 12, Ufa, 450008, Russia

 PDF, 1074 kB

DOI: 10.18287/2412-6179-CO-1474

Pages: 301-310.

Full text of article: Russian language.

Abstract:
One of the well-known problems of processing spatial information in applied areas is its pronounced spatial anisotropy, due to both the uneven distribution of data sources over the earth's surface and their temporary non-operability due to technical failures and the human factor. This problem creates tangible obstacles in the study of processes of various origins, on the one hand, and in decision-making processes based on such information, on the other. Thus, geophysical information, in particular, geomagnetic data, which are recorded in real time by a network of magnetic observatories and variation stations around the world, has a pronounced spatial anisotropy. At the same time, the known methods of interpolation, which do not take into account either the features of the described processes / phenomena, or their dependence on external factors, do not effectively cope with the task. In this paper, we propose an approach to adaptive spatial interpolation, the main idea of which is to determine the interpolation methods that are most effective for various combinations of external and internal factors. Further, in the process of interpolation, the desired value is restored by the selected methods based on its geospatial reference and a complex of external factors. By the example of geomagnetic information, the effectiveness of the proposed approach is shown using the developed web-oriented research prototype of a software solution.

Keywords:
geospatial data, spatial interpolation, spatial anisotropy, geoinformation systems and technologies, web GIS.

Citation:
Vorobev AV, Vorobeva GR. Approach to adaptive spatial interpolation of geophysical information. Computer Optics 2025; 49(2): 301-310. DOI: 10.18287/2412-6179-CO-1474.

Acknowledgements:
The work was funded by the Russian Science Foundation under project No. 21-77-30010.

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