Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data
| Author(s) | Pesaresi, Martino | |
| Author(s) | Schiavina, Marcello | |
| Author(s) | Politis, Panagiotis | |
| Author(s) | Freire, Sergio | |
| Author(s) | Krasnodębska, Katarzyna | |
| Author(s) | Uhl, Johannes H. | |
| Author(s) | Carioli, Alessandra | |
| Author(s) | Corbane, Christina | |
| Author(s) | Dijkstra, Lewis | |
| Author(s) | Florio, Pietro | |
| Author(s) | Friedrich, Hannah K. | |
| Author(s) | Gao, Jing | |
| Author(s) | Leyk, Stefan | |
| Author(s) | Lu, Linlin | |
| Author(s) | Maffenini, Luca | |
| Author(s) | Mari-Rivero, Ines | |
| Author(s) | Melchiorri, Michele | |
| Author(s) | Syrris, Vasileios | |
| Author(s) | Van Den Hoek, Jamon | |
| Author(s) | Kemper, Thomas | |
| Date Accessioned | 2025-01-10T21:03:03Z | |
| Date Available | 2025-01-10T21:03:03Z | |
| Publication Date | 2024-08-30 | |
| Description | This article was originally published in International Journal of Digital Earth. The version of record is available at: https://doi.org/10.1080/17538947.2024.2390454. © 2024 European Union. Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. This article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/17538947.2024.2404284) | |
| 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. | |
| Sponsor | The manuscript displays work that is supported by the European Commission’s Joint Research Centre (EC-JRC) institutional research program 2020-2025. This work is part of the ‘Global Human Settlement Trends and Characteristics’ project [grant no 32161], and includes related scientific collaboration activities such as the ‘Human Planet Initiative’ (HPI). The HPI falls under the Group on Earth Observations (GEO) Strategic Plan 2016-2025. In addition, the activities have been funded by the European Commission’s Directorate-General for Regional and Urban Policy (DG REGIO) [grant no 35864]. Further funding has been provided by the European Commission’s Directorate-General for Defence Industry and Space (DG DEFIS) as part of the European Space programme Copernicus. This includes the implementation of the Emergency Management Service [grant no 35803]. | |
| Citation | Pesaresi, Martino, Marcello Schiavina, Panagiotis Politis, Sergio Freire, Katarzyna Krasnodębska, Johannes H. Uhl, Alessandra Carioli, et al. “Advances on the Global Human Settlement Layer by Joint Assessment of Earth Observation and Population Survey Data.” International Journal of Digital Earth 17, no. 1 (December 31, 2024): 2390454. https://doi.org/10.1080/17538947.2024.2390454. | |
| ISSN | 1753-8955 | |
| URL | https://udspace.udel.edu/handle/19716/35714 | |
| Language | en_US | |
| Publisher | International Journal of Digital Earth | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| Keywords | GHSL | |
| Keywords | geospatial XAI | |
| Keywords | built- up surface | |
| Keywords | population grids | |
| Keywords | degree of urbanization | |
| Keywords | building height | |
| Keywords | built-up volume | |
| Keywords | urban land use | |
| Keywords | settlement morphology | |
| Keywords | built typology | |
| Keywords | Sentinel-2 | |
| Keywords | Copernicus | |
| Title | Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data | |
| Type | Article |
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