DATASET

GHS-POP R2023A - GHS population grid multitemporal (1975-2030)

Collection: GHSL : Global Human Settlement Layer 

Description

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.

Contact

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

Contributors

How to cite

Carioli, Alessandra; Schiavina, Marcello; Freire, Sergio; MacManus, Kytt (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) [Dataset] doi: 10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe

Keywords

GHS POP GHS-POP Global map GPW Population grid Population projections GHSL

Data access

GHS-POP_GLOBE_R2023A
URL 
  • 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.

GHSL website
URL 
  • Project Web site

Publications

Publication 2024
Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and Population Survey data
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
Publication page 
  • Abstract

    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.

Publication 2023
GHSL Data Package 2023
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
Publication page 
  • Abstract

    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.

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
1975-01-01 2030-12-31

Additional information

Published by
European Commission, Joint Research Centre
Created date
2023-04-13
Modified date
2024-11-06
Issued date
2023-05-08
Landing page
http://ghsl.jrc.ec.europa.eu/ 
Language(s)
English
Data theme(s)
Regions and cities, Population and society, Science and technology
Update frequency
irregular
Identifier
http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe
Popularity