#6060. Using bundling to visualize multivariate urban mobility structure patterns in the S?o Paulo Metropolitan Area

July 2026publication date
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Journal’s subject area:
Computer Science Applications;
Computer Networks and Communications;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
Internet-based technologies such as IoT, GPS-based systems, and cellular networks enable the collection of geolocated mobility data of millions of people in large metropolitan areas. In addition, large, public datasets are made available on the Internet by open government programs, providing ways for citizens, NGOs, scientists, and public managers to perform a multitude of data analysis with the goal of better understanding the city dynamics to provide means for evidence-based public policymaking. However, it is challenging to visualize huge amounts of data from mobility datasets. Plotting raw trajectories on a map often causes data occlusion, impairing the visual analysis. Displaying the multiple attributes that these trajectories come with is an even larger challenge. One approach to solve this problem is trail bundling, which groups motion trails that are spatially close in a simplified representation. In this paper, we augment a recent bundling technique to support multi-attribute trail datasets for the visual analysis of urban mobility. Our case study is based on the travel survey from the S?o Paulo Metropolitan Area, which is one of the most intense traffic areas in the world.
Keywords:
Bundling; Data visualization; Open data; Smart cities; Travel surveys; Urban mobility

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