DATASET

GHS-FUA R2019A - GHS functional urban areas, derived from GHS-UCDB R2019A (2015)

Collection: GHSL : Global Human Settlement Layer 

Description

The spatial dataset delineates the boundaries of Functional Urban Areas (FUA) of Urban Centres in 2015. The automatic classification procedure developed in collaboration with the OECD estimates for each 1 sq km populated cells outside Urban Centres (obtained from GHS-POP R2019A) the probability of belonging to the commuting zone (or Area Of Influence, AOI) of the closest Urban Centre (GHS-UCDB R2019A). Cells estimated to be part of the AOI are combined

and polygonized to form estimated FUA (eFUA) boundaries.

Contact

Email
jrc-ghsl-data (at) ec.europa.eu

Contributors

How to cite

Schiavina, Marcello; Moreno-Monroy, Ana; Maffenini, Luca; Veneri, Paolo (2019): GHS-FUA R2019A - GHS functional urban areas, derived from GHS-UCDB R2019A (2015). European Commission, Joint Research Centre (JRC) [Dataset] doi: 10.2905/347F0337-F2DA-4592-87B3-E25975EC2C95 PID: http://data.europa.eu/89h/347f0337-f2da-4592-87b3-e25975ec2c95

Keywords

eFUA FUA Functional Urban Area GHS FUA OECD GHS-FUA GHSL global map

Data access

GHS_FUA_UCDB2015_GLOBE_R2019A
URL 
GHSL website
URL 
  • Project Web site

Publications

Publication 2021
Metropolitan areas in the world. Delineation and population trends
Moreno-Monroy, A., Schiavina, M. and Veneri, P., Metropolitan areas in the world. Delineation and population trends, JOURNAL OF URBAN ECONOMICS, ISSN 0094-1190 (online), 125, 2021, p. 103242, JRC114435.
  • ACADEMIC PRESS INC ELSEVIER SCIENCE, SAN DIEGO, USA
Publication page 
  • Abstract

    This paper presents a novel method to delineate metropolitan areas – or functional urban areas (FUAs) – in the entire world and assesses their population trends. According to the definition developed by the OECD and the EU, FUAs are composed of high-density urban centres with at least 50 thousand people plus their surrounding commuting zones. The latter represent the urban centres’ areas of influence in terms of labour market flows. The proposed method combines a functional and a morphological approach to overcome the dependency on travel-to-work data to define commuting zones and allow a global delineation. It relies on a probabilistic approach and the use of population and travel impedance gridded data across the globe. Results show that around 3.9 billion people, making up 53% of the world population, live in 8,790 FUAs, out of which 17% live in their commuting zones. Between 2000 and 2015, population growth was higher in larger FUAs, highlighting a general trend toward higher concentration of the metropolitan population. Commuting zones grew faster than urban centres, though with heterogeneous patterns across world regions, income levels and metropolitan size.

Publication 2019
GHSL-OECD Functional Urban Areas
Schiavina, M., Moreno-Monroy, A., Maffenini, L. and Veneri, P., GHSL-OECD Functional Urban Areas, EUR 30001 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-11258-7 (online), doi:10.2760/67415 (online), JRC118845.
  • Publications Office of the European Union, Luxembourg, Luxembourg
Publication page 
  • Abstract

    Function Urban Areas (FUAs), as defined by the OECD and the European Union, are sets of contiguous local (administrative) units composed of a ‘city’ and its surrounding, less densely populated local units that are part of the city’s labour market (‘commuting zone’). To be included in the commuting zone, local units should at least 15% of their working population to the city. This definition is limited to the OECD countries and it is subject to both availability of commuting flows data at local level and to the definition of administrative unit boundaries. In the context of international comparability of urban-related statistics and indicators the aim of this task is to propose a FUA definition that does not depend on arbitrary and not harmonized administrative units and scale it to the globe. To pursue this goal it is proposed an automated classification procedure of FUAs based on objective characteristics (distance from the Urban Centre, area and population of the Urban Centre, local population and GDP per capita at national level), to classify areas within and outside FUAs. The automated classification of FUA is done in collaboration with the OECD and supported by DG REGIO. This document describes the public release of the GHSL-OECD Functional Urban Areas 2019 (GHS-FUA).

Publication
Defining the economic boundaries of cities. A global application
Moreno-Monroy, Ana; Schiavina, Marcello; Veneri, Paolo (2018). Defining the economic boundaries of cities. A global application. IAOS-OECD conference "Better statistics for better lives", 19-21 September 2018, Paris
URL 

Geographic areas

World

Spatial coverage

Type Value
GML
<gml:Polygon xmlns:gml="http://www.opengis.net/gml">  <gml:outerBoundaryIs>    <gml:LinearRing>      <gml:coordinates>-180,90 180,90 180,-90 -180,-90 -180,90</gml:coordinates>    </gml:LinearRing>  </gml:outerBoundaryIs></gml:Polygon>
GML
<gml:Polygon xmlns:gml="http://www.opengis.net/gml/3.2">  <gml:exterior>    <gml:LinearRing>      <gml:posList>-180 90 180 90 180 -90 -180 -90 -180 90</gml:posList>    </gml:LinearRing>  </gml:exterior></gml:Polygon>
WKT
POLYGON ((-180 90, 180 90, 180 -90, -180 -90, -180 90))

Temporal coverage

From date To date
2015-01-01 2015-12-31

Additional information

Published by
European Commission, Joint Research Centre
Created date
2019-11-26
Modified date
2022-06-24
Issued date
2019-12-03
Landing page
https://ghsl.jrc.ec.europa.eu/ 
Language(s)
English
Data theme(s)
Regions and cities, Science and technology
Update frequency
irregular
Identifier
http://data.europa.eu/89h/347f0337-f2da-4592-87b3-e25975ec2c95
Popularity