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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["This collection provides access to multiple versions of nighttime lights datasets, including DMSP-OLS and VIIRS."],["DMSP-OLS datasets offer global nighttime lights data, with versions focusing on radiance-calibrated imagery, time series analysis, and a consistent, corrected dataset (CCNL)."],["VIIRS datasets provide annual and monthly composites of nighttime lights, with options for stray light correction and varying versions (V2.1, V2.2)."],["These datasets allow for the analysis of nighttime light emissions, enabling studies on urbanization, economic activity, and environmental changes."],["Data from both DMSP-OLS and VIIRS are available for different time periods, allowing for temporal analysis and change detection."]]],["The core content focuses on various nighttime light datasets, including the Consistent and Corrected Nighttime Lights (CCNL) and multiple versions of the Defense Meteorological Program (DMSP) Operational Line-Scan System (OLS) and Visible Infrared Imaging Radiometer Suite (VIIRS) data. These datasets capture visible and near-infrared emissions at night, offering both annual and monthly composites. Data processing involves removing factors such as sunlit, moonlit, and cloudy pixels to produce refined, cloud-free composites. The CCNL dataset mitigates issues like inter-annual inconsistency and saturation.\n"]]
