JRC Data Catalogue
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GHS-POP R2023A - GHS population grid multitemporal (1975-2030)

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The spatial raster dataset depicts the distribution of population, expressed as the number of people per cell. Residential population estimates between 1975 and 2020 in 5 years intervals and projections to 2025 and 2030 derived from CIESIN GPWv4.11 were disaggregated from census or administrative units to grid cells, informed by the distribution, density, and classification of built-up as mapped in the Global Human Settlement Layer (GHSL) global layer per corresponding epoch.

This dataset is an update of the product released in 2022. Major improvements are the following: use of built-up volume maps (GHS-BUILT-V R2022A); use of more recent and detailed population estimates derived from GPWv4.11 integrating both UN World Population Prospects 2022 country population data and World Urbanisation Prospects 2018 data on Cities; revision of GPWv4.11 population growthrates by convergence to upper administrative level growthrates; systematic improvement of census coastlines; systematic revision of census units declared as unpopulated; integration of non-residential built-up volume information (GHS-BUILT-V_NRES R2023A); spatial resolution of 100m Mollweide (and 3 arcseconds in WGS84); projections to 2030.

Contributors

How to cite

Schiavina, Marcello; Freire, Sergio; Alessandra Carioli; MacManus, Kytt (2026): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre [Dataset] doi: 10.2905/JRC.CXKEDRR; 10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe

Keywords

GHS POPGHS-POPGHSLGlobal mapGPWPopulation gridPopulation projections

Data access

TIFF

TIFF – Tagged Image File Format – is a computer file format for storing raster graphics images, popular among graphic artists, the publishing industry and photographers. TIFF is widely supported by scanning, faxing, word processing, optical character recognition, image manipulation, desktop publishing and page-layout applications. The format was created by Aldus Corporation for use in desktop publishing.

Downloadable file

A downloadable file for the dataset.

Use conditions
European Commission reuse notice

According to the European Commission reuse notice, reuse is authorised, provided the source is acknowledged. The reuse policy of the European Commission is implemented by the Decision of 12 December 2011. The general principle of reuse can be subject to conditions which may be specified in individual copyright notices. Therefore users are advised to refer to the copyright notices of the individual websites maintained under Europa and of the individual documents. Reuse is not applicable to documents subject to intellectual property rights of third parties.

Access conditions
No limitations

Anybody can directly and anonymously access the data, without being required to register or authenticate.

  • GHS population grid, derived from GPW4.11, for 1975-2030 (5yrs interval). Values are expressed as decimals (Float). The data is published at medium and low resolution (100m and 1km respectively) in World Mollweide (EPSG:54009). The grids in WGS84 (EPSG:4326) are produced from the 100m World Mollweide grids and have a spatial resolution of 3 arc-seconds and 30 arc-seconds. The compressed ZIP file contain TIF files and short documentation.

Other resources

HTML

HTML is the standard markup language used to create web pages and its elements form the building blocks of all websites.

Use conditions
European Commission reuse notice

According to the European Commission reuse notice, reuse is authorised, provided the source is acknowledged. The reuse policy of the European Commission is implemented by the Decision of 12 December 2011. The general principle of reuse can be subject to conditions which may be specified in individual copyright notices. Therefore users are advised to refer to the copyright notices of the individual websites maintained under Europa and of the individual documents. Reuse is not applicable to documents subject to intellectual property rights of third parties.

Access conditions
No limitations

Anybody can directly and anonymously access the data, without being required to register or authenticate.

  • Project Web site

Publications

Publication
SCHIAVINA, M., MELCHIORRI, M., PESARESI, M., POLITIS, P., CARNEIRO FREIRE, S.M., MAFFENINI, L., FLORIO, P., EHRLICH, D., GOCH, K., CARIOLI, A., UHL, J., TOMMASI, P. and KEMPER, T., GHSL Data Package 2023, Publications Office of the European Union, Luxembourg, 2023, doi:10.2760/098587 (online),10.2760/20212 (print), JRC133256.
Publications Office of the European Union, Luxembourg, Luxembourg
  • The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics and knowledge describing the human presence on planet Earth. It operates in a fully open and free data and methods access policy. The knowledge generated with the GHSL is supporting the definition, the public discussion and the implementation of European policies and the monitoring of international frameworks such as the 2030 Development Agenda. The GHSL are the core data set of the Exposure Mapping Component under the Copernicus Emergency Management Service. GHSL data continue to support the GEO Human Planet Initiative (HPI) that is committed to developing a new generation of measurements and information products providing new scientific evidence and a comprehensive understanding of the human presence on the planet and that can support global policy processes with agreed, actionable and goal-driven metrics. The Human Planet Initiative relies on a core set of partners committed in coordinating the production of the global settlement spatial baseline data.

    This document describes the public release of the GHSL Data Package 2023 (GHS P2023). The release provides improved built-up (including surface, volume and height) and population products as well as a new settlement model and classification of administrative and territorial units according to the Degree of Urbanisation.

Publication
PESARESI, M., SCHIAVINA, M., POLITIS, P., FREIRE, S., GOCH, K., UHL, J.H., CARIOLI, A., CORBANE, C., DIJKSTRA, L., FLORIO, P., FRIEDRICH, H.K., GAO, J., LEYK, S., LINLIN, L., MAFFENINI, L., MARI-RIVERO, I., MELCHIORRI, M., SYRRIS, V., VAN DEN HOEK, J. and KEMPER, T., Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and Population Survey data, INTERNATIONAL JOURNAL OF DIGITAL EARTH, ISSN 1753-8947 (online), 17 (1), 2024, p. 2390454, JRC136539.
TAYLOR & FRANCIS LTD
  • The Global Human Settlement Layer (GHSL) project fosters an enhanced, public understanding of the human presence on Earth. A decade after its inception in the Digital Earth 2020 vision, GHSL is an established project of the European Commission’s Joint Research Centre and an integral part of the Copernicus Emergency Management Service. The 2023 GHSL edition, a result of rigorous research on Earth Observation data and population censuses, contributes significantly to understanding worldwide human settlements. It introduces new elements like 10-m-resolution, sub-pixel estimation of built-up surfaces, global building height and volume estimates, and a classification of residential and non-residential areas, improving population density grids. This paper evaluates the key components of the GHSL, including the Symbolic Machine Learning approach, using novel reference data. These data enable a comparative assessment of GHSL model predictions on the evolution of built-up surface, building heights, and resident population. Empirical evidence suggests that GHSL estimates are the most accurate in the public domain today, e.g. achieving an IoU of 0.98 for the water class, 0.92 for the built-up class, and 0.8 for the non-residential class at 10 m resolution. At 100 m resolution, we find that the MAE of built-up surface estimates corresponds to 6% of the grid cell area, the MAE for the building height estimates is 2.27 m, and we find a total allocation accuracy of 83% for resident population. This paper consolidates the theoretical foundation of the GHSL and highlights its innovative features for transparent Artificial Intelligence, facilitating international decision-making processes.

Spatial coverage

Temporal coverage

From date To date
1975-01-01 2030-12-31

Additional information

Published by
European Commission, Joint Research Centre
Contact email
jrc-ghsl-data (at) ec.europa.eu
Update frequency
irregular

The event occurs at uneven intervals.

Language(s)
English

English is a member of the West Germanic group of the Germanic languages. It is an official language of almost 60 sovereign states and is now a global lingua franca.It is the third-most-common native language in the world and it is widely learned as a second language.

Data theme(s)
Regions and cities

dataset theme covering the domains of regions and cities, where regions is defined by political geography units including sovereign states, subnational administrative areas, and multinational groupings, and cities are characterised as large human settlements

Population and society

dataset theme covering the domains of population and society, where population refers to the total number of people residing within various geographic levels from cities to the global scale, and society denotes a collective of individuals engaged in continuous social interaction within a common territory, often under the same political and cultural norms

Science and technology

dataset theme covering the domains of science and technology, with science being the systematic pursuit of knowledge through testable explanations and predictions across natural, social, and formal disciplines, and technology encompassing the collective techniques, skills, methods, and processes used in producing goods, providing services, or achieving objectives like scientific research

Geographical name(s)
Issued date
2023-05-08
Created date
13 Apr 2023 13:58
Modified date
07 Aug 2025 15:29
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Dataset identifier
Other identifiers
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