Annual global VIIRS nighttime lights dataset is a time series produced from
monthly cloud-free average radiance grids spanning 2013 to 2021.
Data for 2022 are available in theNOAA/VIIRS/DNB/ANNUAL_V22dataset.
An initial filtering step removed sunlit, moonlit and cloudy pixels,
leading to rough composites that contains lights, fires, aurora and
background. The rough annual composites are made on monthly increments and
then combined to form rough annual composites.
The subsequent steps uses the twelve-month median radiance to discard high
and low radiance outliers, filtering out most fires and isolating the
background. Background areas are zeroed out using the data range (DR)
calculated from 3x3 grid cells. The DR threshold for background is indexed
to cloud-cover levels, with higher DR thresholds in areas having low numbers
of cloud-free coverages.
Bands
Pixel Size463.83 meters
Bands
Name
Units
Pixel Size
Description
average
nanoWatts/sr/cm^2
meters
Average DNB radiance values.
average_masked
nanoWatts/sr/cm^2
meters
Average Masked DNB radiance values
cf_cvg
meters
Cloud-free coverages; the total number of observations that
went into each pixel. This band can be used to identify areas with low
numbers of observations where the quality is reduced.
cvg
meters
Total number of observations free of sunlight and moonlight.
maximum
nanoWatts/sr/cm^2
meters
Maximum DNB radiance values.
median
nanoWatts/sr/cm^2
meters
Median DNB radiance values
median_masked
nanoWatts/sr/cm^2
meters
Median masked DNB radiance values.
minimum
nanoWatts/sr/cm^2
meters
Minimum DNB radiance values
Terms of Use
Terms of Use
Colorado School of Mines data, information, and products,
regardless of the method of delivery,
are not subject to copyright and carry no restrictions on their subsequent
use by the public. Once obtained, they may be put to any lawful use. The
forgoing data is in the public domain and is being provided without
restriction on use and distribution.
Citations
Citations:
Elvidge, C.D, Zhizhin, M., Ghosh T., Hsu FC, Taneja J. Annual time series of
global VIIRS nighttime lights derived from monthly averages:2012 to 2019.
Remote Sensing 2021, 13(5), p.922, doi:10.3390/rs13050922doi:10.3390/rs13050922
Annual global VIIRS nighttime lights dataset is a time series produced from monthly cloud-free average radiance grids spanning 2013 to 2021. Data for 2022 are available in the NOAA/VIIRS/DNB/ANNUAL_V22 dataset. An initial filtering step removed sunlit, moonlit and cloudy pixels, leading to rough composites that contains lights, fires, aurora and …
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThe NOAA/VIIRS/DNB/ANNUAL_V21 dataset provides annual global VIIRS nighttime lights data from 2013 to 2021, derived from monthly cloud-free average radiance.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes various bands such as average, average masked, cloud-free coverages, total observations, maximum, median, median masked, and minimum DNB radiance values.\u003c/p\u003e\n"],["\u003cp\u003eData for 2022 is available in a separate dataset (NOAA/VIIRS/DNB/ANNUAL_V22) and 2012 data is excluded due to processing differences.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is provided by the Earth Observation Group at the Colorado School of Mines and is in the public domain, allowing unrestricted use and distribution.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset has a spatial resolution of 463.83 meters and is accessible through the Google Earth Engine platform.\u003c/p\u003e\n"]]],["The annual VIIRS nighttime lights dataset, provided by the Earth Observation Group, spans 2013-2021, with 2022 in a separate dataset. It comprises monthly cloud-free average radiance grids, processed to remove sunlit, moonlit, and cloudy pixels. High and low radiance outliers are discarded to isolate the background, which is then zeroed based on a data range threshold. The dataset includes bands for average, masked average, median, masked median, minimum, and maximum radiance, as well as cloud-free and total observations. The data is public domain.\n"],null,["# VIIRS Nighttime Day/Night Annual Band Composites V2.1\n\nDataset Availability\n: 2012-04-01T00:00:00Z--2021-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines](https://eogdata.mines.edu/products/vnl/#annual_v2)\n\nCadence\n: 1 Year\n\nTags\n:\n[annual](/earth-engine/datasets/tags/annual) [dnb](/earth-engine/datasets/tags/dnb) [eog](/earth-engine/datasets/tags/eog) [lights](/earth-engine/datasets/tags/lights) [nighttime](/earth-engine/datasets/tags/nighttime) [noaa](/earth-engine/datasets/tags/noaa) [population](/earth-engine/datasets/tags/population) [viirs](/earth-engine/datasets/tags/viirs) [visible](/earth-engine/datasets/tags/visible) \n\n#### Description\n\nAnnual global VIIRS nighttime lights dataset is a time series produced from\nmonthly cloud-free average radiance grids spanning 2013 to 2021.\nData for 2022 are available in the\n[NOAA/VIIRS/DNB/ANNUAL_V22](/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V22) dataset.\n\nAn initial filtering step removed sunlit, moonlit and cloudy pixels,\nleading to rough composites that contains lights, fires, aurora and\nbackground. The rough annual composites are made on monthly increments and\nthen combined to form rough annual composites.\n\nThe subsequent steps uses the twelve-month median radiance to discard high\nand low radiance outliers, filtering out most fires and isolating the\nbackground. Background areas are zeroed out using the data range (DR)\ncalculated from 3x3 grid cells. The DR threshold for background is indexed\nto cloud-cover levels, with higher DR thresholds in areas having low numbers\nof cloud-free coverages.\n| **Note:** 2012 data are not yet included because of differences in processing. (A) 201204-201212, and (B) 201204-201303. Only set (B) has masked median and average bands which doesn't follow the pattern there in other year datasets.\n\n### Bands\n\n\n**Pixel Size**\n\n463.83 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|------------------|--------------------|------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `average` | nanoWatts/sr/cm\\^2 | meters | Average DNB radiance values. |\n| `average_masked` | nanoWatts/sr/cm\\^2 | meters | Average Masked DNB radiance values |\n| `cf_cvg` | | meters | Cloud-free coverages; the total number of observations that went into each pixel. This band can be used to identify areas with low numbers of observations where the quality is reduced. |\n| `cvg` | | meters | Total number of observations free of sunlight and moonlight. |\n| `maximum` | nanoWatts/sr/cm\\^2 | meters | Maximum DNB radiance values. |\n| `median` | nanoWatts/sr/cm\\^2 | meters | Median DNB radiance values |\n| `median_masked` | nanoWatts/sr/cm\\^2 | meters | Median masked DNB radiance values. |\n| `minimum` | nanoWatts/sr/cm\\^2 | meters | Minimum DNB radiance values |\n\n### Terms of Use\n\n**Terms of Use**\n\nColorado School of Mines data, information, and products,\nregardless of the method of delivery,\nare not subject to copyright and carry no restrictions on their subsequent\nuse by the public. Once obtained, they may be put to any lawful use. The\nforgoing data is in the public domain and is being provided without\nrestriction on use and distribution.\n\n### Citations\n\nCitations:\n\n- Elvidge, C.D, Zhizhin, M., Ghosh T., Hsu FC, Taneja J. Annual time series of\n global VIIRS nighttime lights derived from monthly averages:2012 to 2019.\n Remote Sensing 2021, 13(5), p.922, doi:10.3390/rs13050922\n [doi:10.3390/rs13050922](https://doi.org/10.3390/rs13050922)\n\n### DOIs\n\n- \u003chttps://doi.org/10.3390/rs13050922\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 dataset = ee.ImageCollection('NOAA/VIIRS/DNB/ANNUAL_V21')\n .filter(ee.Filter.date('2020-01-01', '2021-01-01'));\n\nvar nighttime = dataset.select('maximum');\nvar nighttimeVis = {min: 0.0, max: 60.0};\nMap.setCenter(-77.1056, 38.8904, 8);\nMap.addLayer(nighttime, nighttimeVis, 'Nighttime');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/NOAA/NOAA_VIIRS_DNB_ANNUAL_V21) \n[VIIRS Nighttime Day/Night Annual Band Composites V2.1](/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V21) \nAnnual global VIIRS nighttime lights dataset is a time series produced from monthly cloud-free average radiance grids spanning 2013 to 2021. Data for 2022 are available in the NOAA/VIIRS/DNB/ANNUAL_V22 dataset. An initial filtering step removed sunlit, moonlit and cloudy pixels, leading to rough composites that contains lights, fires, aurora and ... \nNOAA/VIIRS/DNB/ANNUAL_V21, annual,dnb,eog,lights,nighttime,noaa,population,viirs,visible \n2012-04-01T00:00:00Z/2021-01-01T00:00:00Z \n-65 -180 75 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.3390/rs13050922](https://doi.org/https://eogdata.mines.edu/products/vnl/#annual_v2)\n- [https://doi.org/10.3390/rs13050922](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V21)"]]
