Menu
Publications
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2025-25-1-151-159
An approach to solving the problem of geomagnetic data scarcity in decision-making support
Read the full article
Article in Russian
For citation:
Abstract
For citation:
Vorobeva G.R., Vorobev A.V., Farvaev E.F. An approach to solving the problem of geomagnetic data scarcity in decision-making support. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2025, vol. 25, no. 1, pp. 151–159 (in Russian). doi: 10.17586/2226-1494-2025-25-1-151-159
Abstract
One of the main problems of using data in decision-making support is their scarcity in certain spatial points/areas due to the inability to carry out appropriate measurements. An example is the Earth’s magnetic field data (geomagnetic data) which is used to make decisions to reduce the extreme geophysical events negative impact on objects and systems of the technosphere (power lines, communication systems, railway automation, etc.). An analysis of the existing geomagnetic data collection infrastructure from the standpoint of system analysis made it possible to identify incomplete coverage of the monitoring network, which negatively affects decision-making to ensure technosphere security in the relevant spatial areas. Using the example of geomagnetic data, it was revealed that the known interpolation methods, which do not take into account the features of the spatiotemporal characteristics of the processes described by the data and their dependence on external factors, do not deal effectively with the task. To solve this problem, an approach to adaptive spatial interpolation is proposed the main idea of which is the dynamic selection of interpolation methods that are most effective for various factors. For an example of geomagnetic data two factors were chosen: the affiliation of a spatial point to a certain latitude zone and the index of geomagnetic activity in the time period under consideration. To evaluate the proposed solution, a prototype of a web-based application was developed. The experiment was conducted using geomagnetic information from the SuperMAG project. The proposed approach has proved to be more effective than using any separate interpolation method when comparing the root-mean-square errors. Adaptive interpolation proposed in this paper can be used in systems implementing interpolation of geospatial data, as an alternative to standard interpolation methods, in order to increase the accuracy of data recovery. When working with geomagnetic data, the factors considered in this work (latitudinal zones and geomagnetic activity) can be used, but interpolation of data of a different nature will require preliminary analysis to identify significant factors.
Keywords: geospatial data, geomagnetic data, system analysis, spatial interpolation, decision support, web applications
Acknowledgements. The study was carried out with the financial support of the Russian Science Foundation, project No. 25-21-00143, https://rscf.ru/project/25-21-00143/.
References
Acknowledgements. The study was carried out with the financial support of the Russian Science Foundation, project No. 25-21-00143, https://rscf.ru/project/25-21-00143/.
References
- Vorobev A., Soloviev A., Pilipenko V., Vorobeva G., Sakharov Y. An approach to diagnostics of geomagnetically induced currents based on ground magnetometers data. Applied Sciences, 2022, vol. 12, no. 3, pp. 1522. https://doi.org/10.3390/app12031522
- Vorobev A.V., Vorobeva G.R. Approach to assessment of the relative informational efficiency of intermagnet magnetic observatories. Geomagnetism and Aeronomy, 2018, vol. 58, no. 5, pp. 625–628. https://doi.org/10.1134/S0016793218050158
- Fournier A., Aubert J., Lesur V., Thebault E. Physics-based secular variation candidate models for the IGRF. Earth, Planets and Space, 2021, vol. 73, pp. 190. https://doi.org/10.1186/s40623-021-01507-z
- Imboden D., Pfenninger S. Introduction to Systems Analysis Mathematically Modeling Natural Systems. Springer, 2013, 252 p. https://doi.org/10.1007/978-3-642-30639-6
- Brown W., Beggan C., Cox G., Macmillan S. The BGS candidate models for IGRF-13 with a retrospective analysis of IGRF-12 secular variation forecasts. Earth, Planets and Space, 2021, vol. 73. pp. 42. https://doi.org/10.1186/s40623-020-01301-3
- Petrov V., Bondar T. IZMIRAN candidate field model for IGRF-13. Earth, Planets and Space, 2021, vol. 73, pp. 46. https://doi.org/10.1186/s40623-020-01312-0
- Vorobev A.V., Soloviev A.A., Pilipenko V.A., Vorobeva G.R. Interactive computer model for aurora forecast and analysis. Solar-Terrestrial Physics, 2022, vol. 8, no. 2 pp. 84–90. https://doi.org/10.12737/stp-82202213
- Vorobev A.V., Pilipenko V.A., Krasnoperov R.I., Vorobeva G.R., Lorentzen D.A. Short-term forecast of the auroral oval position on the basis of the “virtual globe” technology. Russian Journal of Earth Sciences, 2020, vol. 20. pp. ES6001. https://doi.org/10.2205/2020ES000721
- Gjerloev J.W. The SuperMAG data processing technique. Journal of Geophysical Research: Space Physics, 2012, vol. 117, no. A9, pp. A09213. https://doi.org/10.1029/2012JA017683
- Waters C.L., Gjerloev J.W., Dupont M., Barnes R.J. Global maps of ground magnetometer data. Journal of Geophysical Research: Space Physics, 2015, vol. 120, no. 11. pp. 9651-9660. https://doi.org/10.1002/2015JA021596
- Zhang H., Tian Y., Zhao P. Dispersion curve interpolation based on kriging method. Applied Sciences, 2023, vol. 13, no. 4, pp. 2557. https://doi.org/10.3390/app13042557
- Lebrenz H., Bardossy A. Geostatistical interpolation by quantile kriging. Hydrology and Earth System Sciences, 2019, vol. 23, no. 3, pp. 1633–1648. https://doi.org/10.5194/hess-23-1633-2019
- Alexa M. Conforming weighted Delaunay triangulations. ACM Transactions on Graphics, 2020, vol. 39, no. 6, pp. 1–16. https://doi.org/10.1145/3414685.3417776
- Weng Y., Cao J., Chen Z. Global optimization of optimal Delaunay triangulation with modified whale optimization algorithm. Engineering with Computers, 2024, vol. 40, no. 4, pp. 2595–2616. https://doi.org/10.1007/s00366-023-01928-2
- Huynh T., Tran D., Vu Q., Nguyen L., Design and Implementation of Web Application Based on MVC Laravel Architecture. European Journal of Electrical Engineering and Computer Science, 2022, vol. 6, no. 4. pp. 1–7. https://doi.org/10.24018/ejece.2022.6.4.448
- Rahman M.H., Naderuzzaman M., Kashem M.A., Salahuddin B.M., Mahmud M.Z. Comparative study: performance of MVC frameworks on RDBMS. International Journal of Information Technology and Computer Science, 2024, vol. 16, no. 1, P. 26–34. https://doi.org/10.5815/ijitcs.2024.01.03
- Hule K., Ranawat R. Analysis of different ORM tools for data access object tier generation: a brief study. International Journal of Membrane Science and Technology, 2023, vol. 10, no. 1, pp. 1277–1291. https://doi.org/10.15379/ijmst.v10i1.2842
- Marculescu B., Zhang M., Arcuri A. On the faults found in REST APIs by automated test generation. ACM Transactions on Software Engineering and Methodology, 2022, vol. 31, no. 3, pp. 1–43. https://doi.org/10.1145/3491038
- Golmohammadi A., Zhang M., Arcuri A. Testing RESTful APIs: a survey. ACM Transactions on Software Engineering and Methodology, 2023, vol. 33, no. 1, pp. 1–41. https://doi.org/10.1145/3617175
- Bogner J., Kotstein S., Pfaff T. Do RESTful API design rules have an impact on the understandability of Web APIs? Empirical Software Engineering, 2023, vol. 28, no. 6, pp. 132. https://doi.org/10.1007/s10664-023-10367-y

