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Information-rich visualisation of dense geographical networks

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  • Stefan Hennemann

Abstract

Network information on geographical entities such as cities is frequently analysed numerically, but seldom visualised in an appealing form. Reasons for this include the absence of powerful software that is capable of handling large-scale networks and the layout of this information without extensive visual clutter. In addition, classic network drawing algorithms (e.g. Fruchterman–Reingold) are not optimised for the representation of geographically fixed nodes, and the standard repertoire of cartography is not suited to mapping complex network information. To tackle these issues, a method-mediating circular layout is presented that (1) roughly preserves the geographical information, (2) allows for the drawing of less cluttered relations between the geographical entities, and (3) offers the possibility of including more information on the underlying node and edge attributes when compared to conventional two-dimensional layouts. The data used to show the capacity of the circular layout were devised by the Globalisation and World City (GaWC) research network of 2010, and represents the office networks of globalised advanced producer services firms.

Suggested Citation

  • Stefan Hennemann, 2013. "Information-rich visualisation of dense geographical networks," Journal of Maps, Taylor & Francis Journals, vol. 9(1), pages 68-75, March.
    • Handle: RePEc:taf:tjomxx:v:9:y:2013:i:1:p:68-75
    DOI: 10.1080/17445647.2012.753850
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    Cited by:

    1. Dai, Liang & Derudder, Ben & Liu, Xingjian, 2018. "Transport network backbone extraction: A comparison of techniques," Journal of Transport Geography, Elsevier, vol. 69(C), pages 271-281.
    2. Harry Odell & Eva María Navarro-López & Nuno Pinto & Iain Deas, 2022. "Detecting shifts in metropolitan structure: A spatial network perspective," Environment and Planning B, , vol. 49(7), pages 1912-1928, September.
    3. Ben Derudder, 2021. "Network Analysis of ‘Urban Systems’: Potential, Challenges, and Pitfalls," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 112(4), pages 404-420, September.
    4. Stefan Hennemann & Ben Derudder & Peter J Taylor, 2015. "Cutting the Gordian knot of visualizing dense spatial networks: the case of the world city network, 2013," Environment and Planning A, , vol. 47(6), pages 1332-1340, June.

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