A temporally consistent global 500 m-resolution monthly VIIRS-like nighttime light dataset (1992–2024)

作者：Hongquan Cheng, Mengqing Geng, Xuecao Li, Shijie Li, Min Zhao, Lin Chen, Jie Wang, Peng Gong, Yuyu Zhou · 发表于：Earth system science data · 年份：2026 · DOI：10.5194/essd-18-3449-2026 · 被引用次数：2 · 研究领域：Impact of Light on Environment and Health、Circadian rhythm and melatonin、Optical Wireless Communication Technologies

Abstract. Nighttime light (NTL) data serve as critical indicators of human activities and have been widely applied in urbanization monitoring and socioeconomic analyses. The two most widely used global NTL datasets, derived from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) aboard the Suomi National Polar-orbiting Partnership satellite, differ substantially in spatial resolution and temporal coverage, which hinders their direct integration into a consistent long-term dataset. Previous studies have explored the construction of annual or aggregated NTL data, but these methods often smooth out short-term fluctuations and seasonal variations. Monthly NTL, on the other hand, can provide a more detailed representation of temporal variations. However, the challenge with monthly data lies in maintaining consistent spatial resolution while capturing high-frequency temporal variations tied to economic cycles and seasonal trends, with data gaps persisting, further complicating the generation of continuous, high-resolution monthly NTL datasets. To overcome these challenges, we propose a super-resolution network for DMSP reconstruction, with dedicated pre- and post-processing to generate long-term monthly VIIRS-like NTL products (MVNL). Leveraging multi-modal observations, monthly VIIRS-like products are reconstructed by translating calibrated DMSP data from 1992 to 2013, with 2012 and 2013...