Atmospheric Correction for Night-Time Light Data Using Radiative Transfer Model

Night-time light remote sensing has been widely used in various fields, including human activity analysis, urbanization studies, and economic research. However, Earth’s nighttime environment is very complex so that nighttime light images are seriously affected by atmospheric elements and moonlight. To address this issue, this paper proposed an atmospheric correction algorithm on basis of a newly developed radiative transfer model (RTM) that aims to derive the ground radiance of artificial lights from satellite nighttime light images. The SDGSAT-1 night-time light image of Beijing is used as a case study to demonstrate the effectiveness of the proposed algorithm. Results show that the new algorithm can effectively removes the atmospheric effects and improves the data quality of nighttime light images.