A Pixel-scale Corrected Nighttime Light Dataset (PCNL, 1992-2024) Combining DMSP-OLS and NPP-VIIRS

Updated to 2024! Welcome to download! We proposed a set of DMSP-OLS and NPP-VIIRS inter-correction methods and produced a pixel-scale corrected nighttime light dataset (PCNL). Two sets of reliable global nighttime light datasets were chosen as the basis. CCNL-DMSP (1992-2013) is a consistent and corrected nighttime light dataset produced from DMSP-OLS. CCNL-DMSP mainly solved three problems of DMSP-OLS, namely, interannual inconsistency, saturation and blooming. The annual VNL-VIIRS dataset available on the Earth Observation Group website was also used, and the monthly median masked data of V21/V22 was selected. Using filtering and employing outlier removal, VNL-VIIRS has removed sunlit, moonlit and cloudy pixels, and has discarded biomass burning pixels. PCNL shows a great temporal and spatial consistency at both the pixel scale and the regional scale. Please refer to the paper for detailed information. Li, S., Cao, X*., Zhao, C., Jie, N., Liu, L., Chen, X., Cui, X., (2023). Developing a Pixel-Scale Corrected Nighttime Light Dataset (PCNL, 1992–2021) Combining DMSP-OLS and NPP-VIIRS. Remote Sensing, 15, 3925. https://doi.org/10.3390/rs15163925 Other recent publications using PCNL: Li, S., Cao, X.*, (2024). Monitoring the modes and phases of global human activity development over 30 years: Evidence from county-level nighttime light. International Journal of Applied Earth Observation and Geoinformation, 126, 103627. https://doi.org/10.1016/j.jag.2023.103627 Li, S., Cao, X.*, Liu, L., Li, A., (2025). Inequality of divided and shared socio-economic resources in 15-minute cities of China. Geography and Sustainability, 100337. https://doi.org/10.1016/j.geosus.2025.100337