FlyTsViz: A Flight Time Series Data Visual Analytics System Based on Reduction Method

The rapid development of unmanned aerial vehicles (UAVs) and other low-altitude aircraft technologies has dramatically increased the volume of generated flight time series data. These data contain important operational and performance information which is crucial for further analysis and mining, providing valuable insights for system optimization and decision-making. To address this challenge, we develop FlyTsViz, a time series reduction-based visualization and analysis system specifically designed for flight data. The system integrates data preprocessing and interactive visualization features, enabling users to efficiently identify and understand complex patterns within flight data. FlyTsViz employs an aggregation-based data reduction method, significantly reducing the visualization burden while maintaining the characteristics and analytical accuracy of the data. Experimental results show that the aggregation algorithm used by FlyTsViz balances data processing time with visualization integrity and outperforms fixed-interval sampling, uniform sampling, and MaxMin aggregation, thus improving the overall performance of the system. FlyTsViz has been successfully applied to flight data analysis and can be easily extended to time series data from other domains, offering robust support across various industries.