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The large volume of data automatically collected by smart card fare systems offers a rich source of information regarding daily human activities with a high resolution of spatial and temporal representation. This provides an opportunity for aiding transport planners and policy-makers to plan transport systems and cities more responsively. However, there are currently limitations when it comes to understanding the secondary activities of individual commuters. Accordingly, in this paper, we propose a framework to detect and infer secondary activities from individuals' daily travel patterns from the smart card data and reduce the use of conventional surveys. First, we proposed a 'heuristic secondary activity identification algorithm', which uses commuters' primary locations (home & work) and the direction (from & to) information to identify secondary activities for individuals. The algorithm provides a high-level classification of the activity types as before-work, midday and after-work activity patterns of individuals. Second, this classification is semantically enriched using Points of Interests to provide meaningful insights into individuals' travel purposes and mobility in an urban environment. Lastly, using the transit data of London as a case study, the model is compared with a volunteer survey to demonstrate its effectiveness and offering a cost-effective method to travel demand research. [ABSTRACT FROM AUTHOR]

In this paper we provide a detailed geographical analysis of the role of the New York-London (NYLON) connection in the world city network. We find that its pre-eminence is much greater and much more diverse than previously considered. Our analysis draws on a data collection of the worldwide office networks of producer services firms across cities in 2018, and applies a purposeful combination of principal components analysis and network analysis to identify the relative importance of city-dyads in different regional geographies of globalization. We review the role of NYLON in the the different city sub-nets thus identified, and provide a more focused discussion of NYLON's role in the production of three of these. In a short conclusion, we consider the meaning of our results for the broader literature. [ABSTRACT FROM AUTHOR]

The map presented in this paper shows the effect of congestion on daily accessibility in the London metropolitan area on Wednesdays. Because of its dynamic nature, it is challenging to both calculate the effects of this phenomenon and to represent it clearly on simple maps. Although we can use many traditional techniques for this purpose, they are usually static, and they may lose some essential information on the effects studied. In this paper, we used two cartographic techniques rarely used in accessibility studies – cartograms and 3D maps, which we believe can achieve a more striking representation in static and animations of both the traffic-induced spatial distortion and the accessibility levels obtained. The results are presented in two animated maps and some snapshots of them – static maps. Both types of maps reinforce each other: Together, they can properly show the direct space–time link between congestion and accessibility, and can, therefore, give a more detailed overview of the consequences of this phenomenon. [ABSTRACT FROM AUTHOR]