Colour remote sensing of the impact of artificial light at night (II): Calibration of DSLR-based images from the International Space Station

Miguel, Alejandro Sánchez de; Zamorano, J.; Aubé, Martin; Bennie, Jonathan; Gallego, J.; Ocaña, F.; Pettit, Donald R.; Stefanov, William L.; Gaston, Kevin J.

doi:10.1016/j.rse.2021.112611

Cited by 31 publications

(15 citation statements)

References 50 publications

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“…We believe that the bands of future sensors must contain at least three bands in the visible range, as well as a near-infrared band (IR). With three bands, the ISS and UAV data can overcome the limitations of traditional mono-spectral VIIRS/DNB data [46][47][48]. Whether for urban lighting or light pollution, a single wide waveband is no longer able to meet our requirements.…”

Section: Spectral Resolutionmentioning

confidence: 98%

“…Three different ISS image parts in the study areas were first selected to obtain the optimal thresholding values of brightness for separating bright urban areas and lowlight suburban areas (Figure 3). We focused on only low-light suburban areas to avoid duplicating efforts, given that numerous studies have shown that ISS imagery is very useful to map lighting types and land surface within bright urban areas [45,47,48]. In the image of Calgary, the optimal thresholding values were found to be 35 for the red band, 30 for the yellow band, and 25 for the blue band, respectively.…”

Section: Retrieving the Low-light Suburban Areasmentioning

confidence: 99%

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The Potential of Moonlight Remote Sensing: A Systematic Assessment with Multi-Source Nightlight Remote Sensing Data

Liu¹,

Zhang²,

Wang

et al. 2021

Remote Sensing

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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.

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Section: Spectral Resolutionmentioning

confidence: 98%

Section: Retrieving the Low-light Suburban Areasmentioning

confidence: 99%

The Potential of Moonlight Remote Sensing: A Systematic Assessment with Multi-Source Nightlight Remote Sensing Data

Liu¹,

Zhang²,

Wang

et al. 2021

Remote Sensing

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“…Here, challenges are posed by remote sensing approaches that are almost always only proxies for the ecological variable of interest. Night-time satellite data are limited in spatial, spectral and temporal resolution, but color imaging from the international space station ISS, airborne measurements, and particularly UAVs have the potential to fill the existing gaps in ALAN related biodiversity research (Bouroussis and Topalis, 2020;Levin et al, 2020;Sánchez de Miguel et al, 2021). A key component to improving the utility of these data would be research efforts that can translate what remotely sensed values could represent for conditions at ground level, where first steps have been taken but uncertainties remain high (Simons et al, 2020).…”

Section: Interdisciplinary Barriers To Measuring Nocturnal Lightmentioning

confidence: 99%

11 Pressing Research Questions on How Light Pollution Affects Biodiversity

et al. 2021

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Artificial light at night (ALAN) is closely associated with modern societies and is rapidly increasing worldwide. A dynamically growing body of literature shows that ALAN poses a serious threat to all levels of biodiversity—from genes to ecosystems. Many “unknowns” remain to be addressed however, before we fully understand the impact of ALAN on biodiversity and can design effective mitigation measures. Here, we distilled the findings of a workshop on the effects of ALAN on biodiversity at the first World Biodiversity Forum in Davos attended by several major research groups in the field from across the globe. We argue that 11 pressing research questions have to be answered to find ways to reduce the impact of ALAN on biodiversity. The questions address fundamental knowledge gaps, ranging from basic challenges on how to standardize light measurements, through the multi-level impacts on biodiversity, to opportunities and challenges for more sustainable use.

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“…Monochrome and RGB imagery of artificial light emissions with nearly worldwide coverage is presently provided by several on-orbit radiometers (Elvidge et al 2017(Elvidge et al , 2021Levin et al 2020;? ;Zheng et al 2018) as well as by the Crew Earth Observation program of the International Space Station (Sánchez de Miguel et al 2019Miguel et al , 2021Stefanov et al 2017). These inputs are expected to be enough for computing world hemispheric sky brightness maps with a level of accuracy comparable to that already attained by their zenith counterparts (Falchi et al 2016).…”

Section: Artificial Light Sourcesmentioning

confidence: 99%

Towards a global map of the artificial all-sky brightness

Kocifaj,

Bará,

Falchi

2022

Preprint

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Modeling the hemispherical night sky brightness of anthropogenic origin is a demanding computational challenge, due to the intensive calculations required to produce all-sky maps with fine angular resolution including high-order scattering effects. We present in this Letter a physically consistent, semi-analytic two-parameter model of the all-sky radiance produced by an artificial light source that encodes efficiently the spectral radiance in all directions of the sky above the observer. The two parameters of this function are derived from the state of the atmosphere, the distance to the observer, and the source's angular and spectral emission pattern. The anthropogenic all-sky radiance at any place on Earth can be easily calculated by adding up the contributions of the surrounding artificial sources, using the information available from nighttime satellite imagery and ground-truth lighting inventories. This opens the way for the elaboration of a global world map of the artificial all-sky brightness.

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Colour remote sensing of the impact of artificial light at night (II): Calibration of DSLR-based images from the International Space Station

Cited by 31 publications

References 50 publications

The Potential of Moonlight Remote Sensing: A Systematic Assessment with Multi-Source Nightlight Remote Sensing Data

The Potential of Moonlight Remote Sensing: A Systematic Assessment with Multi-Source Nightlight Remote Sensing Data

11 Pressing Research Questions on How Light Pollution Affects Biodiversity

Towards a global map of the artificial all-sky brightness

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