Atmospheric Correction for Nighttime Light Image Using Radiative Transfer Model

Nighttime light (NTL) remote sensing data have been widely used in various fields, such as human activity analysis, urbanization studies, and economic evaluation. However, Earth’s nighttime environment is very complex so that the NTL images are seriously affected by atmospheric effects and moonlight. This complexity primarily stems from the numerous atmospheric scattering and absorption, as well as the incoming moonlight, which can significantly distort and contaminate NTL observed by the satellite and consequently reduce the precision and stability of NTL data. In order to improve the quantitative quality of the NTL data, this article proposes an innovative atmospheric correction algorithm that leverages the nighttime radiative transfer model (nRTM) considering both atmospheric effect and moonlight effect to get ground radiance of artificial lights from satellite NTL images. This model takes into account the complex interactions between light and the atmosphere. By simulating these processes, the algorithm is able to separate the contributions of atmospheric scattering and absorption from the original NTL images. To demonstrate the effectiveness of the proposed algorithm, this article takes the Sustainable Development Goals Science Satellite 1 (SDGSAT-1) NTL image of Beijing as a representative case study of atmospheric correction. By comparing the corrected and uncorrected images, it is evident that the atmospheric correction significantly improves the quality of the NTL data and the ground nighttime lighting information becomes clearer and more accurate, effectively removing noise interference and enhancing data reliability. Moreover, it also found that the high-pressure sodium (HPS) lamps and LED lamps in the NTL images presented different radiance values and spectral shapes that can be helpful for classifying different lamps.