Population and built-up density - Cities and FUAs — Urbanised area by country
<p align="justify">This dataset provides indicators of population density and built-up area in FUAs and cities.</p> <h3>Data sources and methodology</h3> <p align="justify"> FUA and city surfaces are calculated from FUA and city shapefiles, using GIS tools. Built-up data uses GHSL built-up surface grids <a...
What the numbers show
Population and built-up density - Cities and FUAs — Urbanised area is currently reported for 2 countries. The highest value is 11 Square kilometres in Armenia; the lowest is 7 Square kilometres in Luxembourg.
The median across all reporting countries is 9 Square kilometres, and the mean is 9 Square kilometres.
The gap between the highest and lowest reporting country is a factor of about 2.
Population and built-up density - Cities and FUAs — Urbanised area: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Armenia | 11 Square kilometres | 2030 | up 10.0% | rising |
| 2 | Luxembourg | 7 Square kilometres | 2030 | unchanged | rising |
About this data
<p align="justify">This dataset provides indicators of population density and built-up area in FUAs and cities.</p> <h3>Data sources and methodology</h3> <p align="justify"> FUA and city surfaces are calculated from FUA and city shapefiles, using GIS tools. Built-up data uses GHSL built-up surface grids <a href=https://doi.org/10.2760/098587>(European Commission, GHSL Data Package 2023)</a>. Population counts are extracted from the <a href=https://data-explorer.oecd.org/vis?df[ds]=Design&df[id]=DSD_FUA_DEMO%40DF_AGE_SEX&df[ag]=OECD.CFE.EDS>Population by age and sex - FUAs and cities</a> dataset. GHSL is used as it provides harmonised, globally consistent coverage at fine spatial resolution (100 m), enabling the production of comparable subnational indicators on built-up areas. </p> <p align="justify"> These estimates may differ from official subnational built-up statistics due to differences in methodologies, such as top down remote-sensing based estimations versus bottom up cadastral or administrative data, along with differences in satellite imagery sources, spatial resolution, and model accuracy used to detect and classify built up areas. </p> <h3>Defining FUAs and cities</h3> <p align="justify">The OECD, in cooperation with the EU, has developed a harmonised <a href="https://www.oecd.org/en/data/datasets/oecd-definition-of-cities-and-functional-urban-areas.html">definition of functional urban areas</a> (FUAs) to capture the economic and functional reach of cities based on daily commuting patterns <a href=https://doi.org/10.1787/9789264174108-en>(OECD, 2012)</a>. FUAs consist of: <ol> <li><b>A city</b> – defined by urban centres in the degree of urbanisation, adapted to the closest local administrative units to define a city.</li> <li><b>A commuting zone</b> – including all local areas where at least 15% of employed residents work in the city.</li> </ol> The delineation process includes: <ul> <li>Assigning municipalities surrounded by a single FUA to that FUA.</li> <li>Excluding non-contiguous municipalities.</li> </ul> The definition identifies 1 285 FUAs and 1 402 cities in all OECD member countries except Costa Rica and three accession countries.</p> <h3>Cite this dataset</h3> <p>OECD Regions, cities and local areas database (<a href="http://data-explorer.oecd.org/s/1e6">Population and built-up density - Cities and FUAs</a>), <a href=http://oe.cd/geostats>http://oe.cd/geostats</a></p> <h3>Further information</h3> <ul> <li> <a href=https://localdataportal.oecd.org/>OECD Local Data Portal </a> </li> <li> <a href=https://www.oecd.org/en/publications/oecd-regions-and-cities-at-a-glance-2024_f42db3bf-en.html/>OECD Regions and Cities at a Glance </a> </li> </ul> <p align="justify">For questions and/or comments, please email <a href="mailto:CitiesStat@oecd.org">CitiesStat@oecd.org</a>