Cet ensemble de données raster spatiales représente la répartition mondiale des hauteurs de bâtiments avec une résolution de 100 m, pour l'année 2018. Les données d'entrée utilisées pour prédire la hauteur des bâtiments sont le modèle numérique de surface global ALOS (30 m), les données de la mission topographique radar de la navette spatiale de la NASA (30 m) et un composite d'images Sentinel-2 global à partir de données L1C pour la période 2017-2018.
Pour en savoir plus sur les produits de données GHSL, consultez le rapport sur le package de données GHSL 2023, dans lequel la couche de hauteur des bâtiments est appelée "Average Net Building Height" (ANBH, hauteur nette moyenne des bâtiments).
Le projet Global Human Settlement Layer (GHSL) est soutenu par la Commission européenne, le Centre commun de recherche et la Direction générale de la politique régionale et urbaine.
Bracelets
Taille des pixels 100 mètres
Bandes de fréquences
Nom
Unités
Taille des pixels
Description
built_height
m
mètres
Hauteur moyenne des bâtiments par cellule de grille
Conditions d'utilisation
Conditions d'utilisation
Le GHSL a été produit par le Centre commun de recherche de la Commission européenne en tant que données ouvertes et sans frais. La réutilisation est autorisée à condition que la source soit mentionnée. Pour en savoir plus, veuillez lire les conditions d'utilisation (Avis de réutilisation et de droits d'auteur de la Commission européenne).
Méthodologie : 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.
Cet ensemble de données raster spatiales représente la répartition mondiale des hauteurs de bâtiments avec une résolution de 100 m, pour l'année 2018. Les données d'entrée utilisées pour prédire la hauteur des bâtiments sont le modèle numérique de surface global ALOS (30 m), les données de la mission topographique radar de la navette spatiale de la NASA (30 m) et un …
[null,null,[],[[["\u003cp\u003eThis dataset provides a global view of building heights at a 100-meter resolution for the year 2018.\u003c/p\u003e\n"],["\u003cp\u003eBuilding heights were estimated using ALOS, SRTM, and Sentinel-2 data.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is provided by the European Commission Joint Research Centre (JRC) and is freely available for reuse with attribution.\u003c/p\u003e\n"],["\u003cp\u003eAverage building height is represented in meters within a single band named 'built_height'.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore and analyze this dataset further within the Google Earth Engine platform.\u003c/p\u003e\n"]]],["The dataset provides the global distribution of building heights for 2018 at a 100-meter resolution, sourced from the EC JRC. It utilizes ALOS, SRTM, and Sentinel-2 data. Data access is available via Earth Engine using the provided snippet `ee.ImageCollection(\"JRC/GHSL/P2023A/GHS_BUILT_H\")`. The \"built_height\" band measures average building height in meters per grid cell. This data is free to use with proper source acknowledgement.\n"],null,["# GHSL: Global building height 2018 (P2023A)\n\nDataset Availability\n: 2018-01-01T00:00:00Z--2018-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [EC JRC](https://ghsl.jrc.ec.europa.eu/ghs_buH2023.php)\n\nTags\n:\n[alos](/earth-engine/datasets/tags/alos) [building](/earth-engine/datasets/tags/building) [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [dem](/earth-engine/datasets/tags/dem) [ghsl](/earth-engine/datasets/tags/ghsl) [height](/earth-engine/datasets/tags/height) [jrc](/earth-engine/datasets/tags/jrc) [population](/earth-engine/datasets/tags/population) [sdg](/earth-engine/datasets/tags/sdg) [sentinel2-derived](/earth-engine/datasets/tags/sentinel2-derived) [srtm](/earth-engine/datasets/tags/srtm) [urban](/earth-engine/datasets/tags/urban) \n\n#### Description\n\nThis spatial raster dataset depicts the global distribution of building\nheights at a resolution of 100 m, referred to the year 2018. The input data\nused to predict building heights are the ALOS Global Digital Surface Model\n(30 m), the NASA Shuttle Radar Topographic Mission data (30 m), and a global\nSentinel-2 image composite from L1C data for the period 2017-2018.\n\nMore information about the GHSL data 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),\nwhere the building height layer is referred to as the Average Net Building\nHeight (ANBH).\n\nThe Global Human Settlement Layer (GHSL) project is supported by the\nEuropean Commission, Joint Research Centre, 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 | Units | Pixel Size | Description |\n|----------------|-------|------------|---------------------------------------|\n| `built_height` | m | meters | Average building height per grid cell |\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 : Pesaresi, Martino; Politis, Panagiotis (2023): GHS-BUILT-H\n R2023A - GHS building height, derived from AW3D30, SRTM30, and Sentinel2\n composite (2018). European Commission, Joint Research Centre (JRC)\n [PID: http://data.europa.eu/89h/85005901-3a49-48dd-9d19-6261354f56fe](http://data.europa.eu/89h/85005901-3a49-48dd-9d19-6261354f56fe)\n [doi:10.2905/85005901-3A49-48DD-9D19-6261354F56FE](https://doi.org/10.2905/85005901-3A49-48DD-9D19-6261354F56FE)\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/10.2905/85005901-3A49-48DD-9D19-6261354F56FE\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_BUILT_H/2018\");\nvar built = image.select('built_height');\nvar visParams = {\n min: 0.0,\n max: 12.0,\n palette: ['000000', '0d0887', '7e03a8', 'cc4778', 'f89540', 'f0f921'],\n};\n\nMap.setCenter(2.349014, 48.864716, 10);\nMap.addLayer(built, visParams, 'Average building height [m], 2018');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GHSL_P2023A_GHS_BUILT_H) \n[GHSL: Global building height 2018 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_H) \nThis spatial raster dataset depicts the global distribution of building heights at a resolution of 100 m, referred to the year 2018. The input data used to predict building heights are the ALOS Global Digital Surface Model (30 m), the NASA Shuttle Radar Topographic Mission data (30 m), and a ... \nJRC/GHSL/P2023A/GHS_BUILT_H, alos,building,built,built-environment,builtup,copernicus,dem,ghsl,height,jrc,population,sdg,sentinel2-derived,srtm,urban \n2018-01-01T00:00:00Z/2018-12-31T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.2905/85005901-3A49-48DD-9D19-6261354F56FE](https://doi.org/https://ghsl.jrc.ec.europa.eu/ghs_buH2023.php)\n- [https://doi.org/10.2905/85005901-3A49-48DD-9D19-6261354F56FE](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_H)"]]
