The Lines and the Land: A Classification of Route Maps Using Multivariate Analysis

Click to increase image sizeClick to decrease image size

Acknowledgements

This research has been made possible by an ARC5 fellowship (region Rhône-Alpes, France) and an Arthur and Janet Holzheimer Fellowship in the History of Cartography at the Newberry Library.

Notes

1 Allan MacEachren, ‘A Linear View of the World: Strip Maps as a Unique Form of Cartographic Representation,’ The American Cartographer 13, no. 1 (1986): 7–25, at 8.

2 For an introduction to road and route mapping, see James R. Akerman, ‘Route Map,’ 1368-1370, and James R. Akerman, Claudia R. Asch, Thomas J. Bassett, Wolfgang Lierz, Dorothy F. Prescott, ‘Road Mapping,’ 1339–1365, in Cartography in the Twentieth Century, ed. Mark Monmonier, Vol. 6 of The History of Cartography (Chicago: The University of Chicago Press, 2015); Catherine Delano-Smith, ‘Milieus of Mobility: Itineraries, Route Maps, and Road Maps,’ in James R. Akerman, ed., Cartographies of Travel and Navigation (Chicago: The University of Chicago Press, 2006), 16–68; and Jordana Dym, Mapping Travel: The Origins and Conventions of Western Journey Maps (Leiden: Brill, 2021).

3 To my knowledge, the application of this method to maps has only been tried in Alexander Kent and Peter Vujakovic, ‘Stylistic Diversity in European State 1:50 000 Topographic Maps,’ The Cartographic Journal 46, no. 3 (2009): 179–213.

4 For a more comprehensive description of the method and results, see Quentin Morcrette, ‘Tracer la route. Les cartes d’itinéraire du papier à l’écran, usages et représentations : contribution pour une étude diachronique comparée (France/États-Unis)’ (PhD Thesis, Université Lumière Lyon 2, 2018), Chapter 4, esp. 185–197.

5 On the numerous works on this subject, see, for example: John-Brian Harley, ‘Silences and secrecy: The Hidden Agenda of Cartography in Early Modern Europe,’ Imago Mundi 40 (1988): 57–76.

6 Christopher Colles, A survey of the roads of the United States of America (New York: C. Colles, 1789), David Rumsey Map Collection.

7 XlStat is a statistical data analysis add-on created by Lumivero for Microsoft Excel.

8 This analysis uses the first four axes, which explain 67% of adjusted inertia from the ACM.

9 See François Husson, et al., Analyse de données avec R (Rennes: Presses Universitaires de Rennes, 2009); Romuald Le Lan, ‘Analyse de données et classification sur données d’enquête : choix sur les variables, le nombre de classes et le nombre d’axes,’ Les IX Journées de Méthodologie Statistique de l’INSEE, Paris, 14–16 mars, 2005, http://jms-insee.fr/2005/S12_2_ACTE_LE-LAN_JMS2005.pdf.

10 Sanders Lena, L’analyse des données appliquée à la géographie (Montpellier: G.I.P Reclus, 1989).

11 Explaining 53% of adjusted inertia by classes differentiation from the ahc (47% of inertia is intra-class). The aggregation criteria used is the Ward method, minimising intra-class variation, and maximising inter-class variation; the Euclidean distance was used as the measure of dissimilarity.

12 The central object of a class is the object closest to the barycenter of that class. It might thus be considered as exemplary of the characteristics of this class.

13 Statistical tests (chi-square tests and Fisher’s exact tests) were carried out on each class to help determine the most characteristic aspects of classes.

14 For a definition of hodological space, see, Laurent Gagnol, ‘Pour une géographie nomade. Perspectives anthropogéographiques à partir de l'expérience des Touaregs Kel Ewey (Aïr - Niger)’ (PhD Thesis, Université Joseph-Fourier, Grenoble I, 2009).

15 For more on the egocentric dimension of digital maps, see Tristan Thielmann, ‘“You Have Reached your Destination!” Position positioning and superpositioning of space through car navigation systems,’ Social Geography 2 (2007): 63–75.