L'ensemble de données LandScan, fourni par le laboratoire national d'Oak Ridge (ORNL), offre un ensemble de données complet et haute résolution sur la répartition de la population mondiale. Il constitue une ressource précieuse pour un large éventail d'applications. En s'appuyant sur des techniques de modélisation spatiale de pointe et des sources de données géospatiales avancées, LandScan fournit des informations détaillées sur le nombre et la densité de population avec une résolution de 30 secondes d'arc. Il permet ainsi d'obtenir des insights précis et à jour sur les modes d'établissement humain à travers le monde. Grâce à sa précision et à sa granularité, LandScan est utile dans divers domaines tels que l'urbanisme, l'intervention en cas de catastrophe, l'épidémiologie et la recherche environnementale. Il s'agit d'un outil essentiel pour les décideurs et les chercheurs qui cherchent à comprendre et à résoudre divers problèmes sociétaux et environnementaux à l'échelle mondiale.
Bracelets
Taille des pixels 1 000 mètres
Bandes de fréquences
Nom
Min
Max
Taille des pixels
Description
b1
0*
21171*
mètres
Nombre de personnes estimé
* valeur minimale ou maximale estimée
Conditions d'utilisation
Conditions d'utilisation
Les ensembles de données Landscan sont concédés sous licence internationale Creative Commons Attribution 4.0. Les utilisateurs sont libres d'utiliser, de copier, de distribuer, de transmettre et d'adapter l'œuvre à des fins commerciales et non commerciales, sans restriction, à condition que la source soit clairement attribuée.
Citations
Citations :
Sims, K., Reith, A., Bright, E., Kaufman, J., Pyle, J., Epting, J., Gonzales, J., Adams, D., Powell, E., Urban, M., & Rose, A. (2023). LandScan Global 2022 [ensemble de données]. Oak Ridge National Laboratory. https://doi.org/10.48690/1529167
L'ensemble de données LandScan, fourni par le laboratoire national d'Oak Ridge (ORNL), offre un ensemble de données complet et haute résolution sur la répartition de la population mondiale. Il constitue une ressource précieuse pour un large éventail d'applications. En s'appuyant sur des techniques de modélisation spatiale de pointe et des sources de données géospatiales avancées, LandScan fournit des informations détaillées sur le nombre d'habitants et…
[null,null,[],[[["\u003cp\u003eThe LandScan dataset provides high-resolution global population distribution data from 2000 to 2022.\u003c/p\u003e\n"],["\u003cp\u003eDeveloped by Oak Ridge National Laboratory (ORNL), it offers population counts and density at a 30 arc-second resolution (approximately 1km).\u003c/p\u003e\n"],["\u003cp\u003eLandScan data is valuable for applications like urban planning, disaster response, and epidemiology.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is licensed under Creative Commons Attribution 4.0 International, allowing for free use with attribution.\u003c/p\u003e\n"],["\u003cp\u003eUsers can access and analyze the LandScan dataset within Google Earth Engine.\u003c/p\u003e\n"]]],["The LandScan dataset, from Oak Ridge National Laboratory (ORNL), provides global population distribution data from 2000 to 2023. It uses spatial modeling to offer population counts and density at a 30 arc-second resolution, with a 1000-meter pixel size. The data is accessible in the Earth Engine via an ImageCollection, and the band 'b1' details estimated population counts, varying from 0 to 21171. Users can utilize it for free under a Creative Commons license.\n"],null,["# LandScan Population Data Global 1km\n\ninfo\n\n\nThis dataset is part of a Community Catalog, and not managed by Google Earth Engine.\n\nContact gee-community-catalog@googlegroups.com\n\nfor bugs or [view more datasets](https://developers.google.com/earth-engine/datasets/community/sat-io)\nfrom the Awesome GEE Community Catalog Catalog. [Learn more about Community datasets](/earth-engine/datasets/community). \n[](https://gee-community-catalog.org/) \n\nCatalog Owner\n: Awesome GEE Community Catalog\n\nDataset Availability\n: 2000-01-01T00:00:00Z--2023-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [Oak Ridge National Laboratory](https://www.ornl.gov/)\n\nTags\n:\n[community-dataset](/earth-engine/datasets/tags/community-dataset) [demography](/earth-engine/datasets/tags/demography) [landscan](/earth-engine/datasets/tags/landscan) [population](/earth-engine/datasets/tags/population) [sat-io](/earth-engine/datasets/tags/sat-io) \n\n#### Description\n\nThe LandScan dataset, provided by the Oak Ridge National Laboratory (ORNL), offers a comprehensive and high-resolution global population distribution dataset that serves as a valuable resource for a wide range of applications. Leveraging state-of-the-art spatial modeling techniques and advanced geospatial data sources, LandScan provides detailed information on population counts and density at a 30 arc-second resolution, enabling precise and up-to-date insights into human settlement patterns across the globe. With its accuracy and granularity, LandScan supports diverse fields such as urban planning, disaster response, epidemiology, and environmental research, making it an essential tool for decision-makers and researchers seeking to understand and address various societal and environmental challenges on a global scale.\n\n### Bands\n\n\n**Pixel Size**\n\n1000 meters\n\n**Bands**\n\n| Name | Min | Max | Pixel Size | Description |\n|------|-----|---------|------------|----------------------------|\n| `b1` | 0\\* | 21171\\* | meters | Estimated Population count |\n\n\\* estimated min or max value\n\n### Terms of Use\n\n**Terms of Use**\n\nLandscan datasets are licensed under the Creative Commons Attribution 4.0\nInternational License. Users are free to use, copy, distribute, transmit,\nand adapt the work for commercial and non-commercial purposes, without\nrestriction, as long as clear attribution of the source is provided.\n\n### Citations\n\nCitations:\n\n- Sims, K., Reith, A., Bright, E., Kaufman, J., Pyle, J., Epting, J., Gonzales, J., Adams, D., Powell, E., Urban, M., \\& Rose, A. (2023). LandScan Global 2022 \\[Data set\\]. Oak Ridge National Laboratory. https://doi.org/10.48690/1529167\n\n### DOIs\n\n- \u003chttps://doi.org/10.48690/1529167\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 landscan_global =\n ee.ImageCollection('projects/sat-io/open-datasets/ORNL/LANDSCAN_GLOBAL');\nvar popcount_intervals = '\u003cRasterSymbolizer\u003e' +\n ' \u003cColorMap type=\"intervals\" extended=\"false\" \u003e' +\n '\u003cColorMapEntry color=\"#CCCCCC\" quantity=\"0\" label=\"No Data\"/\u003e' +\n '\u003cColorMapEntry color=\"#FFFFBE\" quantity=\"5\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#FEFF73\" quantity=\"25\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#FEFF2C\" quantity=\"50\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#FFAA27\" quantity=\"100\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#FF6625\" quantity=\"500\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#FF0023\" quantity=\"2500\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#CC001A\" quantity=\"5000\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003cColorMapEntry color=\"#730009\" quantity=\"185000\" label=\"Population Count (Estimate)\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003c/RasterSymbolizer\u003e';\n\n// Define a dictionary which will be used to make legend and visualize image on\n// map\nvar dict = {\n 'names': [\n '0', '1-5', '6-25', '26-50', '51-100', '101-500', '501-2500', '2501-5000',\n '5001-185000'\n ],\n 'colors': [\n '#CCCCCC', '#FFFFBE', '#FEFF73', '#FEFF2C', '#FFAA27', '#FF6625', '#FF0023',\n '#CC001A', '#730009'\n ]\n};\n\n// Create a panel to hold the legend widget\nvar legend = ui.Panel({style: {position: 'bottom-left', padding: '8px 15px'}});\n\n// Function to generate the legend\nfunction addCategoricalLegend(panel, dict, title) {\n // Create and add the legend title.\n var legendTitle = ui.Label({\n value: title,\n style: {\n fontWeight: 'bold',\n fontSize: '18px',\n margin: '0 0 4px 0',\n padding: '0'\n }\n });\n panel.add(legendTitle);\n\n var loading = ui.Label('Loading legend...', {margin: '2px 0 4px 0'});\n panel.add(loading);\n\n // Creates and styles 1 row of the legend.\n var makeRow = function(color, name) {\n // Create the label that is actually the colored box.\n var colorBox = ui.Label({\n style: {\n backgroundColor: color,\n // Use padding to give the box height and width.\n padding: '8px',\n margin: '0 0 4px 0'\n }\n });\n\n // Create the label filled with the description text.\n var description = ui.Label({value: name, style: {margin: '0 0 4px 6px'}});\n\n return ui.Panel({\n widgets: [colorBox, description],\n layout: ui.Panel.Layout.Flow('horizontal')\n });\n };\n\n // Get the list of palette colors and class names from the image.\n var palette = dict['colors'];\n var names = dict['names'];\n loading.style().set('shown', false);\n\n for (var i = 0; i \u003c names.length; i++) {\n panel.add(makeRow(palette[i], names[i]));\n }\n\n Map.add(panel);\n}\n\naddCategoricalLegend(legend, dict, 'Population Count(estimate)');\n\nMap.addLayer(\n landscan_global.sort('system:time_start')\n .first()\n .sldStyle(popcount_intervals),\n {}, 'Population Count Estimate 2000');\nMap.addLayer(\n landscan_global.sort('system:time_start', false)\n .first()\n .sldStyle(popcount_intervals),\n {}, 'Population Count Estimate 2022');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/sat-io/projects_sat-io_open-datasets_ORNL_LANDSCAN_GLOBAL) \n[LandScan Population Data Global 1km](/earth-engine/datasets/catalog/projects_sat-io_open-datasets_ORNL_LANDSCAN_GLOBAL) \nThe LandScan dataset, provided by the Oak Ridge National Laboratory (ORNL), offers a comprehensive and high-resolution global population distribution dataset that serves as a valuable resource for a wide range of applications. Leveraging state-of-the-art spatial modeling techniques and advanced geospatial data sources, LandScan provides detailed information on population counts and ... \nprojects/sat-io/open-datasets/ORNL/LANDSCAN_GLOBAL, community-dataset,demography,landscan,population,sat-io \n2000-01-01T00:00:00Z/2023-12-31T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.48690/1529167](https://doi.org/https://www.ornl.gov/)\n- [https://doi.org/10.48690/1529167](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/projects_sat-io_open-datasets_ORNL_LANDSCAN_GLOBAL)"]]
