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. 2019 Oct 23;10:4817. doi: 10.1038/s41467-019-12809-y

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Human mobility and hierarchical structure of cities. a Mobility network extracted from North America (New York City shown in inset). Nodes are geographical units (S2 cells) and links are weighted by flows between locations with darker colors corresponding to more intense flows. b Hotspot level calculation using the Loubar method. c-h Maps of hierarchical hotspots for two groups of three metropolitan areas with similar population: c Paris (France) (12.4 million inhabitants), d Bangkok (Thailand) (14.5 million), e Los Angeles (USA) (13.35 million inhabitants), f Alexandria (Egypt) (5.17 million inhabitants), g Santiago (Chile) (7.11 million), and h Sydney (Australia) (5.13 million inhabitants). The color code is the same as in panel b: level 1 (dark red), level 2 (orange), level 3 (yellow), level 4 (green), and level 5 and below (dark blue). The underground map layout is produced using Carto. Map tiles by Carto, under CC BY 3.0. Data by OpenStreetMap, under ODbL