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Multilevel Visual Analysis of Aggregate Geo-Networks.

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    |April 4, 2023
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    GeoNetverse visualizes urban geospatial networks (geo-networks) across multiple levels. This novel technique improves analysis by balancing overview and detail, overcoming limitations of existing methods.

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    Area of Science:

    • Urban analytics
    • Geospatial network visualization
    • Information visualization

    Background:

    • Urban phenomena like pollution and mobility form complex geospatial networks (geo-networks).
    • Existing visualization methods struggle with multi-level analysis of these geo-networks, causing context-switching costs or information loss.
    • Analyzing geo-networks at macro, meso, and micro levels requires effective visualization tools.

    Purpose of the Study:

    • Introduce GeoNetverse, a novel visualization technique for multi-level analysis of aggregate geo-networks.
    • Address the limitations of current visualizations in handling multiple geo-networks.
    • Provide a scalable solution for exploring urban spreading processes.

    Main Methods:

    • Developed GeoNetverse, inspired by metro maps, to balance overview and detail.
    • Employed stacked edges for shared network components.
    • Integrated level-of-detail rendering, progressive crossing minimization, and coloring techniques for visual scalability.

    Main Results:

    • GeoNetverse effectively visualizes aggregate geo-networks at multiple levels.
    • The technique enhances visual scalability, allowing for clearer distinction of individual geo-networks.
    • Evaluations confirmed the multi-perspective analytical capabilities of GeoNetverse.

    Conclusions:

    • GeoNetverse offers a significant advancement in visualizing and analyzing complex urban geospatial networks.
    • The proposed method overcomes key challenges in multi-level geo-network analysis.
    • GeoNetverse provides a scalable and effective tool for urban data exploration.