Abstract
One recent trend in optical remote sensing is to increase observation frequencies. However, there are still challenges on the night side when sunlight is not available. Due to their powerful capabilities in low-light sensing, nightlight satellite sensors have been deployed to capture nightscapes of Earth from space, observing anthropomorphic and natural activities at night. To date, the mainstream of nightlight remote sensing applications has mainly focused on artificial lights, especially within cities or self-luminous bodies, such as fisheries, oil, offshore rigs, etc. Observations taken under moonlight are often discarded or corrected to reduce lunar effects. Some researchers have discussed the possibility of using moonlight as a useful illuminating source at night for the detection of nocturnal features on Earth, but no quantitative analysis has been reported so far. This study aims to systematically evaluate the potential of moonlight remote sensing with mono-spectral Visible Infrared Imaging Radiometer Suite/Day-Night-Band (VIIRS/DNB) imagery and multi-spectral photos taken by astronauts from the International Space Station (ISS), as well as unmanned aerial vehicle (UAV) night-time imagery. Using the VIIRS/DNB, ISS and UAV moonlight images, the possibilities of the moonlight remote sensing were first discussed. Then, the VIIRS/DNB, ISS, UAV images were classified over different non-self-lighting land surfaces to explore the potential of moonlight remote sensing. The overall accuracies (OA) and kappa coefficients are 79.80% and 0.45, 87.16% and 0.77, 91.49% and 0.85, respectively, indicating a capability to characterize land surface that is very similar to daytime remote sensing. Finally, the characteristics of current moonlight remote sensing are discussed in terms of bands, spatial resolutions, and sensors. The results confirm that moonlight remote sensing has huge potential for Earth observation, which will be of great importance to significantly increase the temporal coverage of optical remote sensing during the whole diurnal cycle. Based on these discussions, we further examined requirements for next-generation nightlight remote sensing satellite sensors.
Highlights
IntroductionOne recent trend in optical remote sensing is to increase observation frequencies to meet the urgent need for effectively monitoring of ephemeral events or phenomena on
Using the VIIRS/DNB image and Sentinel-2 mosaic image on the Google Earth Engine platform (GEE), we first assessed the potential of multi-spectral data in land-surface classification under faint lunar illumination (Figure 6)
While some parts of the results are misclassified because of similar spectral characteristics, such as ponds and farmlands, the results prove that unmanned aerial vehicle (UAV) data taken under faint lunar illumination are useful for characterizing land surfaces, those that cannot emit light
Summary
One recent trend in optical remote sensing is to increase observation frequencies to meet the urgent need for effectively monitoring of ephemeral events or phenomena on. Spectroradiometer) sensors can visit the entire Earth surface twice a day through the Remote Sens. Increasing the number of satellites can surely help to increase the temporal resolution of remote sensing observations, but there are still challenges at the night side, when there is no sunlight available to illuminate the Earth surface. Such a situation can be even worse in the polar regions, where sunlight is not available for almost half the year [4]
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