## 4 Results
### The Characteristics of Current Moonlight Remote Sensing  
Finally, the characteristics of current moonlight remote sensing were compared in terms of bands, spatial resolutions, and sensors. The overall classification accuracy with the VIIIRS/DNB imagery was the lowest among the three sets of moonlight remote-sensing imagery. By comparing VIIRS/DNB with the Sentinel-2 images (Figure 13), there are many misclassifications of snowy mountains and rivers, possibly due to their similar backscatter values in the mono-spectral VIIRS/DNB image. The result is limited by the inadequate spectrum information and substantial noise in the mono-spectral data. Thereby, multi-spectral moonlight remote sensing is expected for Earth observations under complex environments at night.  
Figure 12: The classification result of the UAV moonlight mosaic.  
In this study, three image sets with different resolutions (750 m, 30 m, 1 m) were analyzed. Comparing the classification parameters and results, we found that the higher the spatial resolutions were, the more details of the features in an image could be shown, and the UAV image showed unexpectedly vivid details that are even comparable to daytime high-resolution images. Even cars parked in parking lots could be clearly seen on the UAV moonlight image (Figure 14). However, the single-scene data only covered a small amount of land surface. To cover a larger area with more than one scene, the image quality of the multi-scene data could be reduced significantly. Small changes in georeferencing and the surrounding environment caused some land cover types to be misclassified.  
Finally, panchromatic VIIRS/DNB with a spectral coverage from 0.50 m to 0.90 m uses a unique detecting technology. DNB measures night lights, reflected solar, and/or moon light with a large dynamic range of 45,000,000:1, which allows the detection of reflected signals from as low as a quarter full moon illumination to the brightest daylight. To achieve this large dynamic range, it uses four charge coupled device (CCD) arrays in three gain stages.  
As a comparison, consumer-level digital CMOS cameras from Nikon and Hasselblad are used to obtain land surface images under faint lunar illumination (Table 4). It was found that the further the imaging distances are, the larger the International Organization for Standardization (ISO) values are. The exposure time of the UAV imagery is the longest, while that of the ISS imagery is relatively short. The aperture value (AV) and white balance (WB) were F/2.8 and auto-adjustment, respectively. Compared with the VIIRS/DNB sensor, the cost of the UAV and ISS cameras were greatly reduced and they had additional advantages, such as more spectral bands (RGB color) and finer spatial resolutions. However, given the relatively long exposure time, it is impossible to apply a carpeting data acquisition mode to ISS cameras as what is currently implemented for VIIRS/DNB to collect land surface data without gaps under faint lunar illumination.  
Figure 14: Cars in the UAV moonlight image acquired on 20 June 2021.  
Figure 13: Comparison of snowy mountains from the VIIRS/DNB, Sentinel-2 and classification results.