||In recent decades, there has been an increase in artificial lighting in the world due to urbanization and the revolution of LED lighting. Artificial lighting is an indicator of human activity, but can adversely affect natural ecosystems and people due to negative impacts of light pollution. Space-borne and airborne imagery as well as ground-based measurements enable to measure the intensity and spectra of artificial lights. One of the challenges in remote sensing of night-time lights is how to ground truth night-time imagery acquired by satellites, and how much do space-borne measurements represent the brightness as perceived by organisms. Most of the studies on night-time lights to-date were done using panchromatic sensors at large spatial extents, which did not allow to examine intra-urban variation in night light intensity and spectra. The aim of this study was to test the capability of the new Chinese satellite Jilin-1, which is the first commercial satellite to offer multispectral night-light imagery at a spatial resolution below 1 m, to characterize the night-time properties of urban areas. We examined the correspondence between light intensities as measured from different sensors at different spatial resolutions: two Jilin-1 images of the Jerusalem metropolitan area (0.89 m), VIIRS/DNB (500 m), Loujia-1 (130 m), unmanned aerial vehicle (UAV) color image (0.05 m) and hemispherical color photographs taken by a calibrated ground DSLR (digital single-lens reflex camera). In all the comparisons between different remote sensing tools, as the spatial resolution coarsened, the Pearson correlation coefficient increased, reaching > 0.5 (after resampling to 100 m). Stronger correlations were found for the red band, and weaker correlations were found for the blue band, probably due to atmospheric scattering. By identifying specific objects such as buildings and lightings, we found good correspondence () between Jilin-1 and the ground-based measurements of night-time brightness. We further examined the variability of night lights within different land use types and within different ethnic/religion composition of statistical areas. We found that residential areas of Orthodox Jews were characterized with the highest brightness at night compared with residential areas of Arabs in the West Bank that had the lowest brightness. At the statistical zone level (n = 299), more than 50% of the variability in night-time brightness, was explained by land cover properties (NDVI), infrastructure (roads and built volume) and the ethnic/religious composition. In addition, we found that the spectral ratio index which was based on the red and green bands, enabled to better distinguish between land use classes, than the spectral ratio index which was based on the green and blue bands. The availability of night-time multi-spectral imagery at fine spatial resolution now enables to study urban land-use and spatial inequality, and to better understand the factors explaining night-time brightness.