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Bustamante-Calabria, M.; Sánchez de Miguel, A.; Martín-Ruiz, S.; Ortiz, J.-L.; Vílchez, J.M.; Pelegrina, A.; García, A.; Zamorano, J.; Bennie, J.; Gaston, K.J. | ||||
| Title | Effects of the COVID-19 Lockdown on Urban Light Emissions: Ground and Satellite Comparison | Type | Journal Article | ||
| Year | 2021 | Publication | Remote Sensing | Abbreviated Journal | Remote Sensing |
| Volume | 13 | Issue | 2 | Pages | 258 |
| Keywords | Remote Sensing; COVID-19; skyglow | ||||
| Abstract | ’Lockdown’ periods in response to COVID-19 have provided a unique opportunity to study the impacts of economic activity on environmental pollution (e.g., NO2, aerosols, noise, light). The effects on NO2 and aerosols have been very noticeable and readily demonstrated, but that on light pollution has proven challenging to determine. The main reason for this difficulty is that the primary source of nighttime satellite imagery of the earth is the SNPP-VIIRS/DNB instrument, which acquires data late at night after most human nocturnal activity has already occurred and much associated lighting has been turned off. Here, to analyze the effect of lockdown on urban light emissions, we use ground and satellite data for Granada, Spain, during the COVID-19 induced confinement of the city’s population from 14 March until 31 May 2020. We find a clear decrease in light pollution due both to a decrease in light emissions from the city and to a decrease in anthropogenic aerosol content in the atmosphere which resulted in less light being scattered. A clear correlation between the abundance of PM10 particles and sky brightness is observed, such that the more polluted the atmosphere the brighter the urban night sky. An empirical expression is determined that relates PM10 particle abundance and sky brightness at three different wavelength bands. | ||||
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| ISSN | 2072-4292 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | GFZ @ kyba @ | Serial | 3247 | ||
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| Author |
Buxton, R.T.; Seymoure, B.M.; White, J.; Angeloni, L.M.; Crooks, K.R.; Fristrup, K.; McKenna, M.F.; Wittemyer, G. | ||||
| Title | The relationship between anthropogenic light and noise in U.S. national parks | Type | Journal Article | ||
| Year | 2020 | Publication | Landscape Ecology | Abbreviated Journal | Landscape Ecol |
| Volume | 35 | Issue | 6 | Pages | 1371-1384 |
| Keywords | Remote Sensing; Conservation; Skyglow | ||||
| Abstract | Context Natural sound and light regulate fundamental biological processes and are central to visitor experience in protected areas. As such, anthropogenic light and noise have negative effects on both wildlife and humans. While prior studies have examined the distribution and levels of light or noise, joint analyses are rarely undertaken despite their potentially cumulative effects. Objectives We examine the relationship between different types of anthropogenic light and noise conditions and what factors drive correlation, co-occurrences, and divergence between them. Methods We overlaid existing geospatial models of anthropogenic light and noise with landscape predictors in national parks across the continental U.S. Results Overlapping dark and quiet were the most common conditions (82.5–87.1% of park area), representing important refuges for wildlife and human experience. We found low correlation between anthropogenic light and noise (Spearman’s R < 0.25), with the exception of parks with a higher density of roads. Park land within urban areas had the highest probability of co-occurring high light and noise exposure, while park areas with divergent light and noise exposure (e.g., high light and low noise) were most commonly found 5–20 km from urban areas and in parks with roads present. Conclusions These analyses demonstrate that light and noise exposure are not always correlated in national parks, which was unexpected because human activities tend to produce both simultaneously. As such, mitigation efforts for anthropogenic light and noise will require efforts targeting site-specific sources of noise and light. Protecting and restoring sensory environments will involve constructive partnerships capable of reconciling diverse community interests. |
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| ISSN | 0921-2973 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | UP @ altintas1 @ | Serial | 3155 | ||
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| Author |
C-Sanchez, E.; Sanchez-Medina, A.J.; Alonso-Hernandez, J.B.; Voltes-Dorta, A. | ||||
| Title | Astrotourism and Night Sky Brightness Forecast: First Probabilistic Model Approach | Type | Journal Article | ||
| Year | 2019 | Publication | Sensors (Basel, Switzerland) | Abbreviated Journal | Sensors (Basel) |
| Volume | 19 | Issue | 13 | Pages | 2840 |
| Keywords | Society; Astrotourism; Skyglow; night sky brightness; artificial neural networks | ||||
| Abstract | Celestial tourism, also known as astrotourism, astronomical tourism or, less frequently, star tourism, refers to people's interest in visiting places where celestial phenomena can be clearly observed. Stars, skygazing, meteor showers or comets, among other phenomena, arouse people's interest, however, good night sky conditions are required to observe such phenomena. From an environmental point of view, several organisations have surfaced in defence of the protection of dark night skies against light pollution, while from an economic point of view; the idea also opens new possibilities for development in associated areas. The quality of dark skies for celestial tourism can be measured by night sky brightness (NSB), which is used to quantify the visual perception of the sky, including several light sources at a specific point on earth. The aim of this research is to model the nocturnal sky brightness by training and testing a probabilistic model using real NSB data. ARIMA and artificial neural network models have been applied to open NSB data provided by the Globe at Night international programme, with the results of this first model approach being promising and opening up new possibilities for astrotourism. To the best of the authors' knowledge, probabilistic models have not been applied to NSB forecasting. | ||||
| Address | Management Science and Business Economics Group, University of Edinburgh Business School, Edinburgh EH8 9JS, UK | ||||
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| Language | English | Summary Language | Original Title | ||
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| ISSN | 1424-8220 | ISBN | Medium | ||
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| Notes | PMID:31247919 | Approved | no | ||
| Call Number | GFZ @ kyba @ | Serial | 2571 | ||
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| Author |
Cabrera-Barona, P.F.; Bayón, M.; Durán, G.; Bonilla, A.; Mejía, V. | ||||
| Title | Generating and Mapping Amazonian Urban Regions Using a Geospatial Approach | Type | Journal Article | ||
| Year | 2020 | Publication | ISPRS International Journal of Geo-Information | Abbreviated Journal | Ijgi |
| Volume | 9 | Issue | 7 | Pages | 453 |
| Keywords | Remote Sensing | ||||
| Abstract | (1) background: Urban representations of the Amazon are urgently needed in order tobetter understand the complexity of urban processes in this area of the World. So far, limited workthat represents Amazonian urban regions has been carried out. (2) methods: Our study area is theEcuadorian Amazon. We performed a K-means algorithm using six urban indicators: Urban fractaldimension, number of paved streets, urban radiant intensity (luminosity), and distances to theclosest new deforested areas, to oil pollution sources, and to mining pollution sources. We alsocarried out fieldwork to qualitatively validate our geospatial and statistical analyses. (3) results:We generated six Amazonian urban regions representing different urban configurations and processesof major cities, small cities, and emerging urban zones. The Amazonian urban regions generatedrepresent the urban systems of the Ecuadorian Amazon at a general scale, and correspond to theurban realities at a local scale. (4) conclusions: An Amazonian urban region is understood as a set ofurban zones that are dispersed and share common urban characteristics such a similar distance tooil pollution sources or similar urban radiant intensity. Our regionalization model represents thecomplexity of the Amazonian urban systems, and the applied methodology could be transferred toother Amazonian countries. | ||||
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| ISSN | 2220-9964 | ISBN | Medium | ||
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| Notes | Approved | no | |||
| Call Number | GFZ @ kyba @ | Serial | 3115 | ||
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| Author |
Cabrera-Cruz, S.A.; Cohen, E.B.; Smolinsky, J.A.; Buler, J.J. | ||||
| Title | Artificial Light at Night is Related to Broad-Scale Stopover Distributions of Nocturnally Migrating Landbirds along the Yucatan Peninsula, Mexico | Type | Journal Article | ||
| Year | 2020 | Publication | Remote Sensing | Abbreviated Journal | Remote Sensing |
| Volume | 12 | Issue | 3 | Pages | 395 |
| Keywords | Animals | ||||
| Abstract | The distributions of birds during migratory stopovers are influenced by a hierarchy of factors. For example, in temperate regions, migrants are concentrated near areas of bright artificial light at night (ALAN) and also the coastlines of large water bodies at broad spatial scales. However, less is known about what drives broad-scale stopover distributions in the tropics. We quantified seasonal densities of nocturnally migrating landbirds during spring and fall of 2011–2015, using two weather radars on the Yucatan peninsula, Mexico (Sabancuy and Cancun). We tested the influence of environmental predictors in explaining broad-scale bird stopover densities. We predicted higher densities in areas (1) closer to the coast in the fall and farther away in spring and (2) closer to bright ALAN and with lower ALAN intensity in both seasons. We found that birds were more concentrated near the coastline in the fall and away from it in spring around Cancun but not Sabancuy. Counter to our expectations, we detected increased bird densities with increased distance from lights in spring around Sabancuy, and in both seasons around Cancun, suggesting avoidance of bright areas during those seasons. This is the first evidence of broad-scale bird avoidance of bright areas during stopover. | ||||
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| ISSN | 2072-4292 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | GFZ @ kyba @ | Serial | 3004 | ||
| Permanent link to this record | |||||