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A new ranking of the world's largest cities - Do administrative units obscure morphological realities?

Taubenböck, Hannes and Weigand, Matthias and Esch, Thomas and Staab, Jeroen and Wurm, Michael and Mast, Johannes and Dech, Stefan (2019) A new ranking of the world's largest cities - Do administrative units obscure morphological realities? Remote Sensing of Environment, 232, pp. 1-14. Elsevier. doi: 10.1016/j.rse.2019.111353. ISSN 0034-4257.

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Official URL: https://www.sciencedirect.com/science/article/pii/S0034425719303724


With 37 million inhabitants, Tokyo is the world's largest city in UN statistics. With this work we call this ranking into question. Usually, global city rankings are based on nationally collected population figures, which rely on administrative units. Sprawling urban growth, however, leads to morphological city extents that may surpass conventional administrative units. In order to detect spatial discrepancies between the physical and the administrative city, we present a methodology for delimiting Morphological Urban Areas (MUAs). We understand MUAs as a territorially contiguous settlement area that can be distinguished from low-density peripheral and rural hinterlands. We design a settlement index composed of three indicators (settlement area, settlement area proportion and density within the settlements) describing a gradient of built-up density from the urban center to the periphery applying a sectoral monocentric city model. We assume that the urban-rural transition can be defined along this gradient. With it, we re-territorialize the conventional administrative units. Our data basis are recent mapping products derived from multi-sensoral Earth observation (EO) data – namely the Global Urban Footprint (GUF) and the GUF Density (GUF-DenS) – providing globally consistent knowledge about settlement locations and densities. For the re-territorialized MUAs we calculate population numbers using WorldPop data. Overall, we cover the 1692 cities with > 300,000 inhabitants on our planet. In our results we compare the consistently re-territorialized MUAs and the administrative units as well as their related population figures. We find the MUA in the Pearl River Delta the largest morphologically contiguous urban agglomeration in the world with a calculated population of 42.6 million. Tokyo, in this new list ranked number 2, loses its top position. In rank-size distributions we present the resulting deviations from previous city rankings. Although many MUAs outperform administrative units by area, we find that, contrary to what we assumed, in most cases MUAs are considerably smaller than administrative units. Only in Europe we find MUAs largely outweighing administrative units in extent.

Item URL in elib:https://elib.dlr.de/128714/
Document Type:Article
Title:A new ranking of the world's largest cities - Do administrative units obscure morphological realities?
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Taubenböck, HannesUNSPECIFIEDhttps://orcid.org/0000-0003-4360-9126UNSPECIFIED
Weigand, MatthiasUNSPECIFIEDhttps://orcid.org/0000-0002-5553-4152UNSPECIFIED
Esch, ThomasUNSPECIFIEDhttps://orcid.org/0000-0002-5868-9045UNSPECIFIED
Staab, JeroenUNSPECIFIEDhttps://orcid.org/0000-0002-7342-4440145655484
Wurm, MichaelUNSPECIFIEDhttps://orcid.org/0000-0001-5967-1894UNSPECIFIED
Date:August 2019
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 1-14
Series Name:Elsevier
Keywords:City size Urban agglomeration Rank-size distribution Remote sensing Global urban footprint Urban morphology
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
German Remote Sensing Data Center > Land Surface Dynamics
German Remote Sensing Data Center > Leitungsbereich DFD
Deposited By: Taubenböck, Prof. Dr. Hannes
Deposited On:07 Aug 2019 11:02
Last Modified:31 Oct 2023 13:58

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