Urban Mobility Analysis With Mobile Network Data: A Visual Analytics Approach

作者：Senaratne Hansi^*; Mueller Manuel; Behrisch Michael; Lalanne Felipe; Bustos Jimenez Javier; Schneidewind Joern; Keim Daniel; Schreck Tobias

来源：IEEE Transactions on Intelligent Transportation Systems, 2018, 19(5): 1537-1546.

DOI：10.1109/TITS.2017.2727281

• Visual analytics
• mobile network data
• urban dynamics
• spatial and temporal patterns
• mobility
• intelligent transportation system

Urban planning and intelligent transportation management are facing key challenges in today's ever more urbanized world. Providing the right tools to city planners is crucial to cope with these challenges. Data collected from citizens' mobile communication can be used as the foundation for such tools. These kinds of data can facilitate various analysis tasks, such as the extraction of human movement patterns or determining the urban dynamics of a city. City planners can closely monitor such patterns based on which strategic decisions can be taken to improve a city's infrastructure. In this paper, we introduce a novel visual analytics approach for pattern exploration and search in global system for mobile communications mobile networks. We define geospatial and matrix representations of data, which can be interactively navigated. The approach integrates data visualization with suitable data analysis algorithms, allowing to spatially and temporally compare mobile usage, identify regularities, as well as anomalies in daily mobility patterns across regions and user groups. As an extension to our visual analytics approach, we further introduce space-time prisms with uncertain markers to visually analyze the uncertainty of urban mobility patterns.

• 出版日期2018-5
• 单位INRIA