doi: 10.17586/2226-1494-2021-21-2-225-233


An information system for spatial visualization of prognostic and retrospective data on the probability of observing auroras

A. V. Vorobev, G. R. Vorobeva, O. I. Khristodulo


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Vorobev A.V., Vorobeva G.R., Khristodulo O.I. An information system for spatial visualization of prognostic and retrospective data on the probability of observing auroras. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2021, vol. 21, no. 2, pp. 225–233 (in Russian). doi: 10.17586/2226-1494-2021-21-2-225-233



Abstract

The paper presents the results of the development of an open-access web-based system operating in predictive and retrospective modes and providing the user with an interactive tool for monitoring spatial data using the example of visualizing the probability of observing aurora borealis. The work proposes an algorithm for web rendering of spatial images, which provides an increase in the reactivity of web applications due to the formation of a rendered layer on the server side, in contrast to the known approaches solving the problem of interpolation and generation of a spatial layer at the client level. The paper describes the architecture of the information system whose distinctive feature is the combination of various patterns of web programming, i.e. from a monolithic application to a microservice one with elements of a modular architecture of the “model–view–controller” type. The experimental studies allowed establishing an increase in the rendering speed of a spatial image by an average of 8.1 times. The results of the studies have shown that the considered approach to visualization as applied to the geophysical parameters in the region of the auroral oval will provide an increase in the efficiency of studying the dynamics of the auroral oval, which will help to reveal new knowledge regarding the topology of the magnetosphere and its changes, for example, during geomagnetic storms and substorms.


Keywords: web programming, spatial data, spatial visualization, geographic information systems and technologies, data processing

Acknowledgements. The reported study was funded by RFBR, project number 20-07-00011a, RSF, project number 21-77-30010; and the Expert Center “Project Office for the Development of the Arctic” (Agreement No. 217-G dated January 13, 2021), and the Ministry of Education and Science of the Russian Federation as part of the basic part of the state assignment to higher education educational institutions # FEUE-2020-0007.

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