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Modelling Reachability in Transport Networks: Using Alternative Visual Representations in Interactive Linked‐Views to Gain Valuable Insights
Author(s) -
Rehmat Ullah,
Laiq Hasan,
Farman Ullah,
Ajmal Khan,
You-Ze Cho
Publication year - 2021
Publication title -
mobile information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.346
H-Index - 34
eISSN - 1875-905X
pISSN - 1574-017X
DOI - 10.1155/2021/8813163
Subject(s) - reachability , computer science , transport network , variety (cybernetics) , line (geometry) , measure (data warehouse) , visualization , network analysis , perspective (graphical) , human–computer interaction , data science , data mining , theoretical computer science , artificial intelligence , computer network , physics , quantum mechanics , geometry , mathematics
Most people use maps for navigation. Geographic maps visually represent physical distance between locations. These maps sometimes provide a false impression of travel times. Two cities geographically close to each other might be “far apart” in terms of travel time because of slower connections, whereas two cities geographically distant might be “nearby” in terms of travel time because of faster connections. Under such circumstances, visualizing a transport network using time as a distance measure can make the transport network more understandable. This study integrates several (carto)graphic representations—a time line, a distance line, a time prism, a time cartogram, and a geographic map—in an interactive linked-views environment to model reachability in transport networks. A prototype is implemented in a web environment using D3.js. The implementation can be applied to any transport network. In this research, the approach is illustrated with railroad network data for the Dutch province of Overijssel. The solution provides an alternative and insightful perspective for analyzing the data. In addition to complementing a wide variety of methods to visualizing travel times, the approach could be applied in areas such as spatial analysis and transport planning.

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