Using High-Resolution Nighttime Remote Sensing Data to Identify Light Sources in Hong Kong

Shengjie Liu, Chu Wing So, Hung Chak Ho, Qian Shi, Chun Shing Jason Pun

Abstract: Although artificial light at night (ALAN) is essential for nighttime activities, any unregulated and abusive usage can lead to severe degradation in quality of life. In this study, we used high-resolution nighttime remote sensing data of 1-meter spatial resolution to investigate light sources in an urban area of Hong Kong with one million residents. We classified ALAN sources into three categories based on their origins: Building, Park, and Street. We found that 42% of light was from Building, a large fraction of which was unnecessary decorative lighting such as signboards. Lighting from Street accounted for 41%, whereas an unexpectedly high proportion was associated with Park (17%), with sport facilities-related lighting being the dominant contributor. We also detailed one case study which shows the disruptive effects of unregulated usage of LED signboards to the neighboring residential apartments.