Dieses Raster-Dataset stellt eine globale, multitemporale Klassifizierung von ländlichen und städtischen Gebieten dar, bei der die von der UN Statistical Commission empfohlene Methode „Degree of Urbanisation“ (Urbanisierungsgrad) der Stufe I angewendet wird. Sie basiert auf globalen gerasterten Bevölkerungs- und bebauten Flächendaten, die vom GHSL-Projekt für die Epochen 1975–2030 in 5-Jahres-Intervallen generiert wurden.
Die Schichten zum Urbanisierungsgrad wurden durch die Integration von Informationen zur bebauten Fläche aus Landsat- und Sentinel-2-Daten GHS-BUILT-S R2023 und gerasterten Bevölkerungsdaten aus CIESIN GPW v4.11 GHS-POP R2023 generiert.
Dieses Produkt ist eine Aktualisierung der 2023 veröffentlichten Daten basierend auf den Aktualisierungen von GHS-BUILT-S und GHS-POP. Das Abrechnungsmodell wird auf detaillierter Ebene (zweite Ebene – L2) bereitgestellt. Die Klassifizierung der ersten Ebene kann durch Aggregieren von L2 abgerufen werden.
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 1.000 Meter
Bänder
Name
Pixelgröße
Beschreibung
smod_code
Meter
Grad der Urbanisierung
Klassentabelle für smod_code
Wert
Farbe
Beschreibung
-200
#000000
Keine Daten
10
#7ab6f5
Wasser
11
#cdf57a
Ländlich, sehr geringe Bevölkerungsdichte
12
#abcd66
Ländlich mit geringer Bevölkerungsdichte
13
#375623
Cluster für ländliche Gebiete
21
#ffff00
Am Stadtrand oder in der Umgebung einer Stadt
22
#a87000
Halbdichter städtischer Cluster
23
#732600
Dichter städtischer Cluster
30
#ff0000
Stadtzentrum
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.
Dieses Raster-Dataset stellt eine globale, multitemporale Klassifizierung von ländlichen und städtischen Gebieten dar, bei der die von der UN Statistical Commission empfohlene Methode „Degree of Urbanisation“ (Urbanisierungsgrad) der Stufe I angewendet wird. Sie basiert auf globalen gerasterten Bevölkerungs- und Bebauungsdaten, die vom GHSL-Projekt für die Epochen 1975–2030 in 5-Jahres-Intervallen generiert wurden. Die Ebenen zum Urbanisierungsgrad wurden …
[null,null,[],[[["\u003cp\u003eThis dataset provides a global, multitemporal rural-urban classification from 1975 to 2030 in 5-year intervals.\u003c/p\u003e\n"],["\u003cp\u003eIt uses the "Degree of Urbanisation" methodology recommended by the UN Statistical Commission, integrating built-up surface and population data.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is based on Landsat and Sentinel-2 data and is provided at a 1000 meter resolution.\u003c/p\u003e\n"],["\u003cp\u003eIt is produced by the European Commission Joint Research Centre and is available as open and free data for reuse with attribution.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes a classification scheme ranging from "Water" to "Urban centre" to represent varying degrees of urbanization.\u003c/p\u003e\n"]]],["The dataset provides a global, multitemporal rural-urban classification from 1975 to 2030, in 5-year intervals, using the \"Degree of Urbanisation\" methodology. It integrates built-up surface data from Landsat and Sentinel-2 with gridded population data. The dataset is accessible through Google Earth Engine, using the code `ee.ImageCollection(\"JRC/GHSL/P2023A/GHS_SMOD_V2-0\")`. The dataset is provided by the European Commission Joint Research Centre and is open and free to use.\n"],null,["# GHSL: Degree of Urbanization 1975-2030 V2-0 (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://human-settlement.emergency.copernicus.eu/ghs_smod2023.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) [settlement](/earth-engine/datasets/tags/settlement) \n\n#### Description\n\nThis raster dataset represents a global, multitemporal rural-urban\nclassification, applying the \"Degree of Urbanisation\" stage I methodology\nrecommended by UN Statistical Commission, based on global gridded population\nand built-up surface data generated by the GHSL project for the epochs\n1975-2030 in 5-year intervals.\nThe Degree of Urbanisation layers have been generated by integrating\ninformation on built-up surface extracted from Landsat and Sentinel-2 data\n[GHS-BUILT-S R2023](https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S),\nand gridded population data derived from CIESIN GPW v4.11 [GHS-POP R2023](https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_POP).\nThis product is an update of the data released in 2023 based on the updates\nof the GHS-BUILT-S and GHS-POP. The Settlement Model is provided at the\ndetailed level (Second Level - L2). The first-level classification can be\nobtained by aggregating L2.\n\nThe complete information about the GHSL main products can be found in the\n[GHSL Data Package 2023 report](https://human-settlement.emergency.copernicus.eu/documents/GHSL_Data_Package_2023.pdf?t=1727170839)\n\nThe Global Human Settlement Layer (GHSL) project is supported by the European\nCommission, Joint Research Center, and Directorate-General for Regional and\nUrban Policy.\n\n### Bands\n\n\n**Pixel Size**\n\n1000 meters\n\n**Bands**\n\n| Name | Pixel Size | Description |\n|-------------|------------|------------------------|\n| `smod_code` | meters | Degree of urbanization |\n\n**smod_code Class Table**\n\n| Value | Color | Description |\n|-------|---------|--------------------------|\n| -200 | #000000 | No Data |\n| 10 | #7ab6f5 | Water |\n| 11 | #cdf57a | Very low density rural |\n| 12 | #abcd66 | Low density rural |\n| 13 | #375623 | Rural cluster |\n| 21 | #ffff00 | Suburban or peri-urban |\n| 22 | #a87000 | Semi-dense urban cluster |\n| 23 | #732600 | Dense urban cluster |\n| 30 | #ff0000 | Urban centre |\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; Melchiorri, Michele; Pesaresi,\n Martino (2023): GHS-SMOD R2023A - GHS settlement layers, application of\n the Degree of Urbanisation methodology (stage I) to GHS-POP R2023A and\n GHS-BUILT-S R2023A, multitemporal (1975-2030).\n European Commission, Joint Research Centre (JRC)\n [PID: http://data.europa.eu/89h/a0df7a6f-49de-46ea-9bde-563437a6e2ba](http://data.europa.eu/89h/a0df7a6f-49de-46ea-9bde-563437a6e2ba)\n [doi:10.2905/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA](https://doi.org/10.2905/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA)\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/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA\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 image = ee.Image(\"JRC/GHSL/P2023A/GHS_SMOD_V2-0/2030\");\nvar smod = image.select('smod_code');\nMap.setCenter(84, 25, 5);\nMap.addLayer(image, {}, 'Degree of Urbanization');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GHSL_P2023A_GHS_SMOD_V2-0) \n[GHSL: Degree of Urbanization 1975-2030 V2-0 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_SMOD_V2-0) \nThis raster dataset represents a global, multitemporal rural-urban classification, applying the \"Degree of Urbanisation\" stage I methodology recommended by UN Statistical Commission, based on global gridded population and built-up surface data generated by the GHSL project for the epochs 1975-2030 in 5-year intervals. The Degree of Urbanisation layers have been ... \nJRC/GHSL/P2023A/GHS_SMOD_V2-0, ghsl,jrc,population,sdg,settlement \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/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA](https://doi.org/https://human-settlement.emergency.copernicus.eu/ghs_smod2023.php)\n- [https://doi.org/10.2905/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_SMOD_V2-0)"]]
