Dieser Rasterdatensatz stellt die räumliche Verteilung der Wohnbevölkerung dar, ausgedrückt als absolute Anzahl der Einwohner der Zelle.
Die Schätzungen der Wohnbevölkerung zwischen 1975 und 2020 in 5-Jahres-Intervallen und die Prognosen für 2025 und 2030, die aus CIESIN GPWv4.11 abgeleitet wurden, wurden von Volkszählungs- oder Verwaltungseinheiten auf Rasterzellen aufgeschlüsselt. Dabei wurden die Verteilung, das Volumen und die Klassifizierung der bebauten Fläche berücksichtigt, die in den globalen GHSL-Schichten für bebaute Flächen pro Epoche abgebildet sind.
Das Projekt „Global Human Settlement Layer“ (GHSL) wird von der Europäischen Kommission, der Gemeinsamen Forschungsstelle und der Generaldirektion für Regional- und Stadtpolitik unterstützt.
Bänder
Pixelgröße 100 Meter
Bänder
Name
Pixelgröße
Beschreibung
population_count
Meter
Bevölkerungszahl nach Epoche
Nutzungsbedingungen
Nutzungsbedingungen
Das GHSL wurde von der Gemeinsamen Forschungsstelle der Europäischen Kommission als offene und kostenlose Daten erstellt. Die Wiederverwendung ist zulässig, sofern die Quelle angegeben wird. Weitere Informationen finden Sie in den Nutzungsbedingungen (European Commission Reuse and Copyright Notice).
Methodik : Pesaresi, Martino, Marcello Schiavina, Panagiotis Politis,
Sergio Freire, Katarzyna Krasnodebska,
Johannes H. Uhl, Alessandra Carioli et al. (2024). Advances on the
Global Human Settlement Layer by Joint Assessment of Earth Observation
and Population Survey Data. International Journal of Digital Earth 17(1).
doi:10.1080/17538947.2024.2390454.
Dieser Rasterdatensatz stellt die räumliche Verteilung der Wohnbevölkerung dar, ausgedrückt als absolute Anzahl der Einwohner der Zelle. Schätzungen der Wohnbevölkerung zwischen 1975 und 2020 in 5-Jahres-Intervallen und Prognosen für 2025 und 2030, die aus CIESIN GPWv4.11 abgeleitet wurden, wurden von Volkszählungs- oder Verwaltungseinheiten auf Rasterzellen aufgeschlüsselt, …
[null,null,[],[[["\u003cp\u003eThe JRC/GHSL/P2023A/GHS_POP dataset provides global residential population data from 1975 to 2030 at a 100-meter resolution.\u003c/p\u003e\n"],["\u003cp\u003ePopulation estimates from 1975-2020 are based on CIESIN GPWv4.11 and disaggregated to grid cells using built-up area data.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes projections for residential population in 2025 and 2030.\u003c/p\u003e\n"],["\u003cp\u003eThis open and free dataset, produced by the European Commission Joint Research Centre, requires source acknowledgment for reuse.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore and analyze this dataset further using Google Earth Engine.\u003c/p\u003e\n"]]],["The dataset provides spatial distribution of residential population, counting inhabitants per cell from 1975 to 2020 in 5-year intervals, with projections to 2025 and 2030. It's based on CIESIN GPWv4.11 data, disaggregated from census data using GHSL built-up area layers. Data is accessible via the provided Earth Engine snippet, with a 100-meter pixel size, and is freely reusable with source acknowledgment.\n"],null,["# GHSL: Global population surfaces 1975-2030 (P2023A)\n\nDataset Availability\n: 1975-01-01T00:00:00Z--2030-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [EC JRC](https://ghsl.jrc.ec.europa.eu/ghs_pop2023.php)\n\nTags\n:\n [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) [population](/earth-engine/datasets/tags/population) [sdg](/earth-engine/datasets/tags/sdg) \nciesin-derived \n\n#### Description\n\nThis raster dataset depicts the spatial distribution of residential\npopulation, expressed as the absolute number of inhabitants of the cell.\nResidential population estimates between 1975 and 2020 in 5-year intervals\nand projections to 2025 and 2030 derived from CIESIN GPWv4.11 were\ndisaggregated from census or administrative units to grid cells, informed by\nthe distribution, volume, and classification of built-up area as mapped in\nthe [global GHSL built-up surface layers](https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S)\nper epoch.\n\nMore information about the GHSL main products can be found in the\n[GHSL Data Package 2023 report](https://ghsl.jrc.ec.europa.eu/documents/GHSL_Data_Package_2023.pdf?t=1683540422)\n\nThe Global Human Settlement Layer (GHSL) project is supported by the\nEuropean Commission, Joint Research Center, and Directorate-General for\nRegional and Urban Policy.\n\n### Bands\n\n\n**Pixel Size**\n\n100 meters\n\n**Bands**\n\n| Name | Pixel Size | Description |\n|--------------------|------------|---------------------------|\n| `population_count` | meters | Population count by epoch |\n\n### Terms of Use\n\n**Terms of Use**\n\nThe GHSL has been produced by the European Commission Joint Research Centre\nas open and free data. Reuse is authorised, provided the source is\nacknowledged. For more information, please read the use conditions ([European\nCommission Reuse and Copyright Notice](https://ec.europa.eu/info/legal-notice_en)).\n\n### Citations\n\nCitations:\n\n- Dataset : Schiavina, Marcello; Freire, Sergio; Alessandra Carioli;\n MacManus, Kytt (2023): GHS-POP R2023A - GHS population grid\n multitemporal (1975-2030). European Commission, Joint Research Centre\n (JRC)\n [PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe](http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe)\n [doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE](https://doi.org/10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE)\n- Methodology : Pesaresi, Martino, Marcello Schiavina, Panagiotis Politis,\n Sergio Freire, Katarzyna Krasnodebska,\n Johannes H. Uhl, Alessandra Carioli, et al. (2024). Advances on the\n Global Human Settlement Layer by Joint Assessment of Earth Observation\n and Population Survey Data. International Journal of Digital Earth 17(1).\n [doi:10.1080/17538947.2024.2390454](https://doi.org/10.1080/17538947.2024.2390454).\n\n### DOIs\n\n- \u003chttps://doi.org/10.1080/17538947.2024.2390454\u003e\n- \u003chttps://doi.org/10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE\u003e\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar baseChange =\n [{featureType: 'all', stylers: [{saturation: -100}, {lightness: 45}]}];\nMap.setOptions('baseChange', {'baseChange': baseChange});\nvar image1975 = ee.Image('JRC/GHSL/P2023A/GHS_POP/1975');\nvar image1990 = ee.Image('JRC/GHSL/P2023A/GHS_POP/1990');\nvar image2020 = ee.Image('JRC/GHSL/P2023A/GHS_POP/2020');\nvar populationCountVis = {\n min: 0.0,\n max: 100.0,\n palette:\n ['000004', '320A5A', '781B6C', 'BB3654', 'EC6824', 'FBB41A', 'FCFFA4']\n};\nMap.setCenter(8, 48, 7);\nimage1975 = image1975.updateMask(image1975.gt(0));\nimage1990 = image1990.updateMask(image1990.gt(0));\nimage2020 = image2020.updateMask(image2020.gt(0));\nMap.addLayer(image1975, populationCountVis, 'Population count, 1975');\nMap.addLayer(image1990, populationCountVis, 'Population count, 1990');\nMap.addLayer(image2020, populationCountVis, 'Population count, 2020');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GHSL_P2023A_GHS_POP) \n[GHSL: Global population surfaces 1975-2030 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_POP) \nThis raster dataset depicts the spatial distribution of residential population, expressed as the absolute number of inhabitants of the cell. Residential population estimates between 1975 and 2020 in 5-year intervals and projections to 2025 and 2030 derived from CIESIN GPWv4.11 were disaggregated from census or administrative units to grid cells, ... \nJRC/GHSL/P2023A/GHS_POP, ghsl,jrc,population,sdg \n1975-01-01T00:00:00Z/2030-12-31T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE](https://doi.org/https://ghsl.jrc.ec.europa.eu/ghs_pop2023.php)\n- [https://doi.org/10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_POP)"]]
