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    This study introduces StreetWeave, a new framework for visualizing complex street and pedestrian network data. It helps urban planners and researchers analyze diverse spatial information more effectively.

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    Area of Science:

    • Urban Planning and Data Visualization
    • Geospatial Analysis
    • Environmental Science

    Background:

    • Street and pedestrian network visualization is crucial for urban planners, climate researchers, and health experts.
    • Existing visualization techniques lack a unified design framework, complicating data integration and analysis for domain experts.
    • Domain experts often need to combine thematic and physical data across multiple scales, posing challenges for developers and users without programming backgrounds.

    Purpose of the Study:

    • To review existing street-overlaid visualizations and identify common practices and challenges.
    • To develop a design framework that addresses the diverse needs of domain experts in spatial data analysis.
    • To introduce StreetWeave, a declarative grammar for creating custom multivariate spatial network visualizations.

    Main Methods:

    • A systematic review of 45 studies on street-overlaid visualizations.
    • Qualitative coding to analyze analytical purposes, visualization approaches, and data sources.
    • Development of StreetWeave, a declarative grammar for spatial network data visualization.

    Main Results:

    • Identified key aspects of street and pedestrian network visualization usage in practice.
    • Established a design space based on the review findings.
    • Demonstrated the utility of StreetWeave in creating diverse, multi-resolution visualizations for spatial data exploration.

    Conclusions:

    • StreetWeave provides a flexible and accessible approach to designing custom visualizations for multivariate spatial network data.
    • The framework facilitates effective exploration and analysis of complex urban and environmental data.
    • StreetWeave aims to lower entry barriers for domain experts in utilizing advanced spatial data visualization tools.