Ten przestrzenny zbiór danych rastrowych przedstawia globalne rozmieszczenie wysokości budynków w rozdzielczości 100 m w 2018 r. Dane wejściowe używane do przewidywania wysokości budynków to ALOS Global Digital Surface Model (30 m), dane z misji NASA Shuttle Radar Topographic Mission (30 m) oraz globalna kompozycja obrazów z satelity Sentinel-2 pochodzących z danych L1C z lat 2017–2018.
Więcej informacji o produktach danych GHSL znajdziesz w raporcie GHSL Data Package 2023, w którym warstwa wysokości budynków jest określana jako średnia wysokość netto budynku (ANBH).
Projekt Global Human Settlement Layer (GHSL) jest wspierany przez Komisję Europejską, Wspólne Centrum Badawcze oraz Dyrekcję Generalną ds. Polityki Regionalnej i Miejskiej.
Pasma
Rozmiar piksela 100 metrów
Pasma
Nazwa
Jednostki
Rozmiar piksela
Opis
built_height
m
metry
Średnia wysokość budynków w komórce siatki
Warunki korzystania z usługi
Warunki korzystania z usługi
GHSL został opracowany przez Wspólne Centrum Badawcze Komisji Europejskiej jako otwarte i bezpłatne dane. Ponowne wykorzystanie jest dozwolone pod warunkiem podania źródła. Więcej informacji znajdziesz w warunkach korzystania (European
Commission Reuse and Copyright Notice).
Metodologia : Pesaresi, Martino, Marcello Schiavina, Panagiotis Politis, Sergio Freire, Katarzyna Krasnodebska, Johannes H. Uhl, Alessandra Carioli i in. (2024). Postępy w zakresie globalnej warstwy osadnictwa ludzkiego dzięki wspólnej ocenie danych z obserwacji Ziemi i badań ankietowych populacji. International Journal of Digital Earth 17(1).
doi:10.1080/17538947.2024.2390454.
Ten przestrzenny zbiór danych rastrowych przedstawia globalne rozmieszczenie wysokości budynków w 2018 r. z dokładnością do 100 m. Dane wejściowe używane do przewidywania wysokości budynków to ALOS Global Digital Surface Model (30 m), dane z misji NASA Shuttle Radar Topographic Mission (30 m) i …
[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)"]]
