New release: GHS P2022

A new and improved package of datasets have been produced and publicly released on this website


The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet.

The GHSL relies on the design and implementation of new spatial data mining technologies that allow automatic processing, data analytics and knowledge extraction from large amounts of heterogeneous data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources.

The section below contains a list of the new datasets released with the links to the datasheets.

A summary of the information about the new GHSL data released is also available, with links to the datasheets and how to cite and download information.

A series of images depicting the data extraction process of the new data produced
GHSL process (GHS P2022) from satellite imagery to classification of administrative units according to the Degree of Urbanisation in the area of Katowice (Poland). From the left to the right: Sentinel-2 2018 imagery; GHS-BUILT-S 100m built-up detection; GHS-POP 100m population distribution; GHS-SMOD 1000m settlement classification grid; GHS-DUC administrative units classification.

The data

The GHSL Data Package 2022 consists of multitemporal products, that offers an insight into the human presence in the past (epochs from 1975 through 2020, 5 years interval) and the future (2025 and 2030):

  • GHS-BUILT-S R2022A - GHS built-up surface grid, derived from Sentinel-2 composite (2018) and Landsat, multitemporal (1975-2030, 5 years interval)
  • GHS-BUILT-H R2022A - GHS building height, derived from AW3D30, SRTM30, and Sentinel-2 composite (2018)
  • GHS-BUILT-V R2022A - GHS built-up volume grids derived from joint assessment of Sentinel-2, Landsat, and global DEM data, multitemporal (1975-2030, 5 years interval)
  • GHS-BUILT-C R2022A - GHS Settlement Characteristics, derived from Sentinel-2 composite (2018) and other GHS R2022A data
  • GHS-LAND R2022A - Land fraction as derived from Sentinel-2 image composite (2018) and OSM data
  • GHS-POP R2022A - GHS population grid multitemporal (1975-2030, 5 years interval)
  • GHS-SMOD R2022A - GHS settlement layers, application of the Degree of Urbanisation methodology (stage I) to GHS-POP R2022A and GHS-BUILT-S R2022A, multitemporal (1975-2030, 5 years interval)
  • GHS-DUC R2022A - GHS Degree of Urbanisation Classification, application of the Degree of Urbanisation methodology (stage II) to GADM 3.6 layer, multitemporal (1975-2030, 5 years interval)
  • GHS-SDATA R2022A - GHS release R2022A supporting data
  • GHS-BUILT-LAU2STAT R2022A - GHS built-up surface statistics in European LAU2, multitemporal (1975-2020, 5 years interval)

Feel free to Download the GHSL Data Package 2022 report (9.87 MB) containing the complete information about GHSL open data.

Information concerning multi-temporal analyses

Tests with new independent reference data show that GHSL R2022A matches or outperforms other data sources for accuracy in epochs 2018 and 2020 and matches or outperforms also all the other single epochs (1975, 1990, 2000, and 2015) included in the previous release GHSL R2019. The accuracy of the time series and its change rates, however, are lower especially in the rural domain. According to the JRC internal tests, the anomaly is expected to introduce a positive bias in predicted change rates of built-up surfaces and built-up volumes after the year 2000. The positive bias is especially remarkable in the rural domain as set by the GHS-SMOD R2022A. Previous GHSL R2019 was affected by larger omission errors in rural areas compared to R2022A, therefore generating an underestimation of the change rates in the rural domain.

Thus, the use of the GHSL Data Package 2022 (GHS P2022) is currently not recommended for supporting multi-temporal studies and indicators including built-up surfaces, built-up volumes, and population, especially if stratified by GHS-SMOD grid class. Applications relying on data for epochs 2018 and 2020 are not affected.

A new multi-temporal model fixing the anomaly is under study, and a new GHSL R2022B_ R2022B data release is expected for December 2022. Following the publication of the GHS_BUILT R2022B release, the downstream multi-temporal products including the population grids and the degree of urbanisation grids will be updated (GHS-BUILT-S, GHS-BUILT-V, GHS-POP, GHS-SMOD, and GHS-BUILT-LAU2STAT). Versions of the GHSL data in WGS84 and GHS-DUC will be made available only based on GHS_BUILT R2022B.

We thank all GHSL users for your continued support and apologize for the inconvenience.