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Author Cox, D.T.C.; Sánchez de Miguel, A.; Dzurjak, S.A.; Bennie, J.; Gaston, K.J.
Title National Scale Spatial Variation in Artificial Light at Night Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 10 Pages 1591
Keywords Remote Sensing; United Kingdom; National parks; skyglow; VIIRS-DNB; albedo; landcover; light emissions; light pollution; protected areas; skyglow; sky brightness; urbanization
Abstract The disruption to natural light regimes caused by outdoor artificial nighttime lighting has significant impacts on human health and the natural world. Artificial light at night takes two forms, light emissions and skyglow (caused by the scattering of light by water, dust and gas molecules in the atmosphere). Key to determining where the biological impacts from each form are likely to be experienced is understanding their spatial occurrence, and how this varies with other landscape factors. To examine this, we used data from the Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band and the World Atlas of Artificial Night Sky Brightness, to determine covariation in (a) light emissions, and (b) skyglow, with human population density, landcover, protected areas and roads in Britain. We demonstrate that, although artificial light at night increases with human density, the amount of light per person decreases with increasing urbanization (with per capita median direct emissions three times greater in rural than urban populations, and per capita median skyglow eleven times greater). There was significant variation in artificial light at night within different landcover types, emphasizing that light pollution is not a solely urban issue. Further, half of English National Parks have higher levels of skyglow than light emissions, indicating their failure to buffer biodiversity from pressures that artificial lighting poses. The higher per capita emissions in rural than urban areas provide different challenges and opportunities for mitigating the negative human health and environmental impacts of light pollution.
Address Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall TR10 9FE, UK; d.t.c.cox(at )exeter.ac.uk
Corporate Author Thesis
Publisher MDPI Place of Publication Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 2920
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Author Yue, Y.; Tian, L.; Yue, Q.; Wang, Z.
Title Spatiotemporal Variations in Energy Consumption and Their Influencing Factors in China Based on the Integration of the DMSP-OLS and NPP-VIIRS Nighttime Light Datasets Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 7 Pages 1151
Keywords Remote Sensing
Abstract With the speedy growth of economic development, the imbalance of energy supply and demand pose a critical challenge for the energy security of our country. Meanwhile, the increasing and excessive energy consumption lead to the greenhouse effect and atmospheric pollution, greatly threatening the survival and development of human beings. This study integrated two nighttime light remote sensing datasets, namely Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data, to extend the temporal coverage of the study. Then, the distributions of China’s energy consumption from 1995 to 2016 at a 1-km resolution were estimated using different models and the spatiotemporal variations of energy consumption were explored on the basis of the best estimated results. Next, the factors influencing China’s energy intensity on the provincial level were investigated based on the spatial econometric model. The results show that: (1) The integrated nighttime light datasets can be successfully applied to estimate the dynamic changes of energy consumption. Moreover, the panel data model established in our research performed better than the quadratic polynomial model. (2) During the observation period, the energy consumption in China significantly increased, especially in the Yangtze River Delta, the Pearl River Delta, the Beijing–Tianjin–Hebei region, eastern coastal cities, and provincial capitals. (3) Different from the random spatial distribution pattern of energy consumption on the provincial level, the spatial distribution of energy consumption on the prefectural level has significant clusters, and its spatial agglomeration was strengthened year by year during the research period. (4) The spatial Durbin model (SDM) with a spatial fixed effect has been proved to be more suitable to explore the impact mechanism of China’s energy consumption. Among the four socio-economic factors, industrial structure has the greatest impact on the provincial energy intensity in China. Moreover, the changes in industrial structure and foreign direct investment (FDI) can not only influence the local energy intensity but also affect the energy intensity of the neighboring provinces.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2922
Permanent link to this record
 

 
Author Cox, D.T.C.; Sánchez de Miguel, A.; Dzurjak, S.A.; Bennie, J.; Gaston, K.J.
Title National Scale Spatial Variation in Artificial Light at Night Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 10 Pages 1591
Keywords Skyglow; Remote Sensing
Abstract The disruption to natural light regimes caused by outdoor artificial nighttime lighting has significant impacts on human health and the natural world. Artificial light at night takes two forms, light emissions and skyglow (caused by the scattering of light by water, dust and gas molecules in the atmosphere). Key to determining where the biological impacts from each form are likely to be experienced is understanding their spatial occurrence, and how this varies with other landscape factors. To examine this, we used data from the Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band and the World Atlas of Artificial Night Sky Brightness, to determine covariation in (a) light emissions, and (b) skyglow, with human population density, landcover, protected areas and roads in Britain. We demonstrate that, although artificial light at night increases with human density, the amount of light per person decreases with increasing urbanization (with per capita median direct emissions three times greater in rural than urban populations, and per capita median skyglow eleven times greater). There was significant variation in artificial light at night within different landcover types, emphasizing that light pollution is not a solely urban issue. Further, half of English National Parks have higher levels of skyglow than light emissions, indicating their failure to buffer biodiversity from pressures that artificial lighting poses. The higher per capita emissions in rural than urban areas provide different challenges and opportunities for mitigating the negative human health and environmental impacts of light pollution.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2926
Permanent link to this record
 

 
Author Vandersteen, J.; Kark, S.; Sorrell, K.; Levin, N.
Title Quantifying the Impact of Light Pollution on Sea Turtle Nesting Using Ground-Based Imagery Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 11 Pages 1785
Keywords Animals; Skyglow
Abstract Remote sensing of anthropogenic light has substantial potential to quantify light pollution levels and understand its impact on a wide range of taxa. Currently, the use of space-borne night-time sensors for measuring the actual light pollution that animals experience is limited. This is because most night-time satellite imagery and space-borne sensors measure the light that is emitted or reflected upwards, rather than horizontally, which is often the light that is primarily perceived by animals. Therefore, there is an important need for developing and testing ground-based remote sensing techniques and methods. In this study, we aimed to address this gap by examining the potential of ground photography to quantify the actual light pollution perceived by animals, using sea turtles as a case study. We conducted detailed ground measurements of night-time brightness around the coast of Heron Island, a coral cay in the southern Great Barrier Reef of Australia, and an important sea turtle rookery, using a calibrated DSLR Canon camera with an 8 mm fish-eye lens. The resulting hemispheric photographs were processed using the newly developed Sky Quality Camera (SQC) software to extract brightness metrics. Furthermore, we quantified the factors determining the spatial and temporal variation in night-time brightness as a function of environmental factors (e.g., moon light, cloud cover, and land cover) and anthropogenic features (e.g., artificial light sources and built-up areas). We found that over 80% of the variation in night-time brightness was explained by the percentage of the moon illuminated, moon altitude, as well as cloud cover. Anthropogenic and geographic factors (e.g., artificial lighting and the percentage of visible sky) were especially important in explaining the remaining variation in measured brightness under moonless conditions. Night-time brightness variables, land cover, and rock presence together explained over 60% of the variation in sea turtle nest locations along the coastline of Heron Island, with more nests found in areas of lower light pollution. The methods we developed enabled us to overcome the limitations of commonly used ground/space borne remote sensing techniques, which are not well suited for measuring the light pollution to which animals are exposed. The findings of this study demonstrate the applicability of ground-based remote sensing techniques in accurately and efficiently measuring night-time brightness to enhance our understanding of ecological light pollution.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2975
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Author Määttä, I.; Lessmann, C.
Title Human Lights Type Journal Article
Year 2019 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 11 Issue 19 Pages 2194
Keywords Remote Sensing
Abstract Satellite nighttime light data open new opportunities for economic research. The data are objective and suitable for the study of regions at various territorial levels. Given the lack of reliable official data, nightlights are often a proxy for economic activity, particularly in developing countries. However, the commonly used product, Stable Lights, has difficulty separating background noise from economic activity at lower levels of light intensity. The problem is rooted in the aim of separating transient light from stable lights, even though light from economic activity can also be transient. We propose an alternative filtering process that aims to identify lights emitted by human beings. We train a machine learning algorithm to learn light patterns in and outside built-up areas using Global Human Settlements Layer (GHSL) data. Based on predicted probabilities, we include lights in those places with a high likelihood of being man-made. We show that using regional light characteristics in the process increases the accuracy of predictions at the cost of introducing a mechanical spatial correlation. We create two alternative products as proxies of economic activity. Global Human Lights minimizes the bias from using regional information, while Local Human Lights maximizes accuracy. The latter shows that we can improve the detection of human-generated light, especially in Africa.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2999
Permanent link to this record