Interactive Visualization of Big Data of City with SSG Algorithm

Interactive visualization has emerged in visualization research, propelled by advancements in simulation data. It is used in innovative interaction devices and meets evolving visualization interaction requirements. It has the potential to transform data interpretation and user engagement. Air transportation has a vital role in passenger and cargo transportation, significantly influencing regional urban systems. The position of a city within the global or national aviation network is a direct indicator of the global or national urban hierarchy. This network consists of nodes (airports) and lines (airlines), facilitating spatial accessibility among cities. It reflects the hierarchical structure and distribution pattern of the national urban system. In data visualization, particularly its application to air transportation, challenges such as cluttering, the Modifiable Areal Unit Problem (MAUP), and issues related to data normalization exist. To address these challenges, we developed the visualization method of its inherent large datasets by exploring web-access information and utilizing stream smoothing to generate a steady-state genetic algorithm. The method allows for spatial interaction with visualization. The method's effectiveness in handling spatial interaction data was validated for data visualization.