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informacje
Ten zbiór danych jest częścią katalogu społeczności i nie jest zarządzany przez Google Earth Engine.
W przypadku błędów napisz na adres gee-community-catalog@googlegroups.com. Więcej zbiorów danych znajdziesz w katalogu Awesome GEE Community Catalog. Więcej informacji o zbiorach danych społeczności
Zbiór danych LandScan, udostępniany przez Oak Ridge National Laboratory (ORNL), to kompleksowy zbiór danych o rozmieszczeniu ludności na świecie o wysokiej rozdzielczości, który stanowi cenne źródło informacji dla wielu zastosowań. LandScan wykorzystuje najnowocześniejsze techniki modelowania przestrzennego i zaawansowane źródła danych geoprzestrzennych, aby dostarczać szczegółowe informacje o liczbie i gęstości zaludnienia w rozdzielczości 30 sekund łuku. Umożliwia to uzyskanie precyzyjnych i aktualnych informacji o wzorcach osadnictwa na całym świecie. Dzięki swojej dokładności i szczegółowości LandScan wspiera różne dziedziny, takie jak planowanie przestrzenne, reagowanie na katastrofy, epidemiologia i badania środowiskowe. Jest to niezbędne narzędzie dla decydentów i badaczy, którzy chcą zrozumieć i rozwiązać różne problemy społeczne i środowiskowe na skalę globalną.
Pasma
Rozmiar piksela 1000 metrów
Pasma
Nazwa
Minimum
Maks.
Rozmiar piksela
Opis
b1
0*
21171*
metry
Szacunkowa liczba ludności
* szacowana wartość minimalna lub maksymalna
Warunki korzystania z usługi
Warunki korzystania z usługi
Zbiory danych Landscan są objęte licencją Creative Commons Attribution 4.0 International. Użytkownicy mogą bez ograniczeń używać, kopiować, rozpowszechniać, przesyłać i adaptować utwór do celów komercyjnych i niekomercyjnych, pod warunkiem że podane zostanie wyraźne oznaczenie źródła.
Cytaty
Cytowania:
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 [zbiór danych]. Oak Ridge National Laboratory. https://doi.org/10.48690/1529167
Zbiór danych LandScan, udostępniany przez Oak Ridge National Laboratory (ORNL), to kompleksowy zbiór danych o rozmieszczeniu ludności na świecie o wysokiej rozdzielczości, który stanowi cenne źródło informacji dla wielu zastosowań. LandScan wykorzystuje najnowocześniejsze techniki modelowania przestrzennego i zaawansowane źródła danych geoprzestrzennych, aby dostarczać szczegółowe informacje o liczbie ludności i …
[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)"]]
