Interactive Geoinformation System for Dynamic Visualization of Auroral Oval Characteristics Based on Component-Oriented Programming Patterns

Q4 Computer Science Scientific Visualization Pub Date : 2024-05-01 DOI:10.26583/sv.16.2.07
A. Vorobev, G. Vorobeva
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Abstract

The practical need for operational monitoring of the position dynamics of the auroral oval is due to the negative technospheric manifestations of space weather effects observed in this spatial region. However, the well-known software tools for modeling the auroral oval solve this problem inefficiently from the point of view of informativeness and ergonomics. The paper proposes an approach to dynamic visualization of the characteristics of the auroral oval, which is available at the program level in the form of a traditional web application with the ability to render visual elements in the browser, as well as in the format of a standalone service like RESTful-API. The developed solution provides visualization of the following parameters: the probability of observing the glow of the upper layers of the atmosphere with the naked eye, the electric and magnetic potentials of the field in the region of the northern auroral belt, as well as various types of auroral precipitation. It is assumed that the proposed approach will make it possible to significantly increase the efficiency of the study of parameters in the auroral oval region by specialists and scientists in the relevant fields. At the same time, the high internal and low external connectivity of the developed software modules allow them to be integrated into third-party applications of various profiles and purposes.
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基于面向组件编程模式的极光椭圆特征动态可视化交互式地理信息系统
对极光椭圆的位置动态进行业务监测的实际需要是由于在这一空间区域观测到的空间天气效应在技术层的负面表现。然而,从信息量和人机工程学的角度来看,众所周知的极光椭圆建模软件工具解决这一问题的效率不高。本文提出了一种动态可视化极光椭圆形特征的方法,该方法在程序层面以传统网络应用程序的形式提供,能够在浏览器中渲染可视化元素,也可以 RESTful-API 等独立服务的形式提供。开发的解决方案提供以下参数的可视化:肉眼观测到大气上层辉光的概率、北部极光带区域的电场和磁场电位以及各种类型的极光降水。据推测,拟议的方法将有可能大大提高相关领域专家和科学家研究极光椭圆区域参数的效率。同时,所开发的软件模块内部连接性高,外部连接性低,因此可以将其集成到各种规模和用途的第三方应用程序中。
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来源期刊
Scientific Visualization
Scientific Visualization Computer Science-Computer Vision and Pattern Recognition
CiteScore
1.30
自引率
0.00%
发文量
20
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