Monitoring hourly night-time light by an unmanned aerial vehicle and its implications to satellite remote sensing

Satellite-observed night-time light in urban areas has been widely used as an indicator for socioeconomic development and light pollution. Up to present, the diurnal dynamics of city light during the night, which are important to understand the nature of human activity and the underlying variables explaining night-time brightness, have hardly been investigated by remote sensing techniques due to limitation of the revisit time and spatial resolution of available satellites. In this study, we employed a consumer-grade unmanned aerial vehicle (UAV) to monitor city light in a study area located in Wuhan City, China, from 8:08 PM, April 15, 2019 to 5:08 AM, April 16, 2019, with an hourly temporal resolution. By using three ground-based Sky Quality Meters (SQMs), we found that the UAV-recorded light brightness was consistent with the ground luminous intensity measured by the SQMs in both the spatial (R2 = 0.72) and temporal dimensions (R2 > 0.94), and that the average city light brightness was consistent with the sky brightness in the temporal dimension (R2 = 0.98), indicating that UAV images can reliably monitor the city's night-time brightness. The temporal analysis showed that different locations had different patterns of temporal changes in their night-time brightness, implying that inter-calibration of two kinds of satellite images with different overpass times would be a challenge. Combining an urban function map of 18 classes and the hourly UAV images, we found that urban functions differed in their temporal light dynamics. For example, the outdoor sports field lost 97.28% of its measured brightness between 8: 08 PM – 4:05 AM, while an administrative building only lost 4.56%, and the entire study area lost 61.86% of its total brightness. Within our study area, the period between 9:06 PM and 10:05 PM was the period with largest amount of light loss. The spectral analysis we conducted showed that city light colors were different in some urban functions, with the major road being the reddest region at 8:08 PM and becoming even redder at 4:05 AM. This preliminary study indicates that UAVs are a good tool to investigate city light at night, and that city light is very complex in both of the temporal and spatial dimensions, requiring comprehensive investigation using more advanced UAV techniques, and emphasizing the need for geostationary platforms for night-time light sensors.