High-Spatial-Resolution Nighttime Light Dataset Acquisition Based on Volunteered Passenger Aircraft Remote Sensing

Remotely sensed nighttime light (NTL) data provides an opportunity to observe human economic activities at night. However, existing NTL remote sensing data does not sufficiently reflect human activities at a fine resolution. In this study, we obtain a set of NTL data comprising volunteered passenger aircraft nighttime remote sensing (VPAN-RS) imagery by adopting a passenger plane as the remote sensing platform and using low-cost portable photography equipment as sensors. This method demonstrates the advantages of VPAN-RS data in high spatial resolution, frequent revisits, and low cost, which can supplement existing NTL data. The dataset acquired in this study covers 16 cities in China and one city in Japan, with a spatial resolution up to meter level. The data acquisition method and processing workflow are introduced in this article. Quality assessment shows that the reprojection error of the dataset falls within the range from 5–10 pixels, and the geometric error can be within 15 m. Via a comparison to reference data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor of the Suomi-National Polar-Orbiting Partnership (NPP) polar-orbiting satellite, we found that the VPAN-RS data provides more details of city lighting. Additionally, the radiance of the VPAN-RS data suitably fits that of monthly composite NPP/VIIRS data. We further outline an application example of VPAN-RS nighttime imagery, examine the unique challenges associated with VPAN-RS data with a focus on the influence of the image acquisition method on the data quality, and provide an outlook for the future of VPAN-RS data. We conclude that VPAN-RS NTL images are an effective data source for nighttime earth observations and have the potential for various applications.