A high-quality daily nighttime light (HDNTL) dataset for global 600+ cities (2012–2024)

Abstract. Nighttime light (NTL) data at daily scales presents an innovative foundation for monitoring human activities, offering vast potential across various research domains such as urban planning and management, disaster monitoring, and energy consumption. The VNP46A2 dataset, sourced from NPP/VIIRS, has been providing globally corrected daily NTL data since 2012. However, persistent challenges, such as fluctuations in daily NTL series due to spatial mismatch and angular effects, as well as missing data holes, have significantly impacted the accuracy and comprehensiveness of extracting daily NTL changes. To address these challenges, a dataset production framework focusing on error correction, interpolation, and validation was developed. This framework led to the creation of a high-quality daily NTL dataset from 2012 to 2024, named HDNTL, which specifically targets 653 cities with populations predictably exceeding one million in 2025. A comparative analysis with the VNP46A2 dataset revealed promising results in spatial mismatch correction for two sample areas – the airport and flyover (angular effect can be ignored). These areas exhibited reduced fluctuations in HDNTL time series and maintained or strengthened weekly periodicity, which reflects traffic flow dynamics. Furthermore, the correction of angular effects across various urban building landscapes demonstrated sound improvements, mitigating angular effects in different directions and reducing periodicity from the angular impacts. The spatiotemporal interpolation of missing data holes has high similarity with the reference data, as indicated by an R² of 0.98, and it increased the valid pixels of all cities by 15.12%. The HDNTL dataset exhibited enhanced consistency with high-resolution SDGSAT-1 data regarding the NTL change rate and alignment with ground truth data of power outages, showcasing superior performance in short-event detection. Overall, the HDNTL dataset effectively mitigates instability in daily series caused by spatial mismatch and angular effects observed in VNP46A2, improving data comparability across time and space dimensions. This dataset enhances the ability of the NTL to reflect the ground events, providing a more accurate reference for daily-scale nighttime light research. Additionally, the dataset production framework facilitates easy updates from future VNP46A2 products to HDNTL. The HDNTL is openly available at https://doi.org/10.5281/zenodo.14992989 (Pei et al., 2025).