Open Astronomy (Mar 2024)

Multidimensional visualization analysis based on large-scale GNSS data

  • Wang Jingyan,
  • Wang Ronghui,
  • Bo Zhenyong,
  • Li Hengnian,
  • Wang Chong,
  • Fang Yanan

DOI
https://doi.org/10.1515/astro-2022-0037
Journal volume & issue
Vol. 33, no. 1
pp. 93294 – 93314

Abstract

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With the deployment of global navigation systems such as GPS, GLONASS, GALILEO, and BeiDou, and the construction of the global observation network, global navigation satellite system (GNSS) data have greatly expanded. Traditional relational databases and file systems can no longer efficiently store and process GNSS data. In addition, multidimensional, in-depth visual analysis methods for such data are lacking. In this paper, we provide a solution and implement a GNSS data visualization system based on MapV and cesium running on the Hadoop platform, which can effectively solve the problems of the lack of storage and computing resources for these massive multisource heterogeneous data. The proposed system provides multidimensional presentations to show how the space and ground segments of the entire system are organized by analyzing GNSS data.

Keywords