Challenges in remote sensing of night lights – a research agenda for the next decade

In recent years new sensors and products have been developed to advance our capabilities in assessing human activities based on the remote sensing of night lights. Correctly understanding patterns in human activity and land use based on night lights, is key to gauge our advancement in reaching the United Nations Sustainable Development Goals. In this paper I focus on five challenges in remote sensing of night lights. For each of these research challenges I provide a brief review of previous work, and then demonstrate how this challenge can be tackled, using a variety of ground-based sensors (TESS-4C, LANcube, SVC-HR1024 field spectrometer and webcams), UAV imagery, and spaceborne sensors (SDGSAT-1 and VIIRS/DNB). Challenge 1: Providing a cloud mask in future night light missions; Here I demonstrate that using a thermal night time image acquired simultaneously with the night time light image (as in the case for some of the SDGSAT-1 images), a cloud mask can be created, allowing to analyze night lights over cloud-free areas. Challenge 2: Monitoring hourly changes in night lights over a single night. Here I demonstrated that using mobile measurements conducted with a LANcube photometer at different hours, it was possible to detect locations where and when night lights have decreased during the night (e.g. a large sport stadium). In addition, using a citizen science webcam, I showed that hourly changes in night lights can be discerned even from a non-calibrated camera, and that within the city of Jerusalem, where there is a large population of orthodox Jews, certain land uses had less lights during holy days. Challenge 3: Fusing night time imagery from spaceborne sensors with different overpass times and spatial resolution to better understand hourly changes in night lights; merging SDGSAT-1 images (21:30 overpass) and VIIRS/DNB images (01:30 overpass) I was able to map the turning off of street lights across rural areas in France that accelerated since the 2022 energy crisis of Europe. Challenge 4: Estimating the emissions of blue light using night light sensors; here I demonstrated that the measured portion of blue light varies between ground based and spaceborne sensors, and that it is affected by atmospheric scattering; Challenge 5: Quantifying the anisotropy of night light emissions; here I demonstrated that using panoramic images acquired from a UAV at different heights, it is possible to examine how viewing angles affect the light sources that are observed. I conclude that while the number of designated night lights sensors is still limited, with the availability of new multispectral sensors, we can advance in our understanding of the dynamics of human activities at night-time, by fusing data from different sensors, to take advantage of the unique spatial, spectral, temporal and directional capabilities of each of them.