The Consistent and Corrected Nighttime Lights (CCNL) dataset is a reprocessed version of the Defense Meteorological Program (DMSP) Operational Line-Scan System (OLS) Version 4. A series of methods was used to mitigate the impact of inter-annual inconsistency, saturation, and blooming effects and to improve data …
The Defense Meteorological Program (DMSP) Operational Line-Scan System (OLS) has a unique capability to detect visible and near-infrared (VNIR) emission sources at night. This collection contains global nighttime lights images with no sensor saturation. The sensor is typically operated at a high-gain setting to enable …
The Defense Meteorological Program (DMSP) Operational Line-Scan System (OLS) has a unique capability to detect visible and near-infrared (VNIR) emission sources at night. Version 4 of the DMSP-OLS Nighttime Lights Time Series consists of cloud-free composites made using all the available archived DMSP-OLS smooth resolution …
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 …
Annual global VIIRS nighttime lights dataset is a time series produced from monthly cloud-free average radiance grids for 2022. Data for earlier years are available in the NOAA/VIIRS/DNB/ANNUAL_V21 dataset. An initial filtering step removed sunlit, moonlit and cloudy pixels, leading to rough composites that contains …
Monthly average radiance composite images using nighttime data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). As these data are composited monthly, there are many areas of the globe where it is impossible to get good quality data coverage for that month. …
Monthly average radiance composite images using nighttime data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). As these data are composited monthly, there are many areas of the globe where it is impossible to get good quality data coverage for that month. …
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis collection provides access to multiple nighttime lights datasets, including DMSP-OLS and VIIRS, offering various processing levels and temporal resolutions.\u003c/p\u003e\n"],["\u003cp\u003eDMSP-OLS datasets include calibrated lights, nighttime lights time series, and a consistent and corrected version addressing inter-annual inconsistencies and saturation.\u003c/p\u003e\n"],["\u003cp\u003eVIIRS datasets offer annual and monthly composites, with versions accounting for stray light and cloud cover, allowing for diverse nighttime light analyses.\u003c/p\u003e\n"],["\u003cp\u003eThe datasets cover different time periods, with DMSP-OLS spanning 1992-2013 and VIIRS offering data from 2013 onwards, enabling long-term studies of light emissions.\u003c/p\u003e\n"],["\u003cp\u003eThese datasets are valuable for a range of applications, such as studying urbanization, economic activity, light pollution, and environmental changes.\u003c/p\u003e\n"]]],[],null,[]]