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Author Ye, Y.; Xue, X.; Huang, L.; Gan, M.; Tong, C.; Wang, K.; Deng, J.
Title (up) A new perspective to map the supply and demand of artificial night light based on Loujia1-01 and urban big data Type Journal Article
Year 2020 Publication Journal of Cleaner Production Abbreviated Journal Journal of Cleaner Production
Volume 276 Issue Pages 123244
Keywords Remote Sensing
Abstract The notable increase in artificial night light (ANL) induced by the rapid urbanization process has been widely studied, but a deep understanding of the supply and demand status of ANL is still lacking. This paper attempts to map the supply and demand of ANL from the human perspective by using advanced Loujia1-01 nighttime imagery and social media derived population density (PD) data, which provides a new tool for light regulation in urban management. The bivariate clustering based k-means algorithm and template matching technique are integrated to delineate mismatch regions at the block scale to further analyze the underlying reason for unbalanced status. The results showed that the high supply but low demand (HSLD) ANL status was the leading component in the mismatch regions, occupying more than 650,000 ha and mainly occurring in the city center. The HSLD proportion was considerable in terms of public services (44%), commercial (40%), industrial (39%), transportation (56%), and green space areas (53%). Moreover, the HSLD area notably increased 946 ha over time from 18:00 to 22:00. The measurements for validation obtained by field investigation showed highly linear relationship with ANL (R2 = 0.75) and PD (R2 = 0.62), and the mapping results were consistent with the actual conditions. This study reveals the highly unbalanced ANL status, and appeals to planners for the establishment of optimal lighting regulations to alleviate disruptive effects.
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Series Volume Series Issue Edition
ISSN 0959-6526 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 3070
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Author Fasciani, I.; Petragnano, F.; Aloisi, G.; Marampon, F.; Rossi, M.; Francesca Coppolino, M.; Rossi, R.; Longoni, B.; Scarselli, M.; Maggio, R.
Title (up) A new threat to dopamine neurons: the downside of artificial light Type Journal Article
Year 2020 Publication Neuroscience Abbreviated Journal Neuroscience
Volume in press Issue Pages in press
Keywords Review; Human Health; Parkinson's disease; artificial light; dopamine neurons; melatonin; opsins; photoactivation
Abstract Growing awareness of adverse impacts of artificial light on human health has led to recognize light pollution as a significant global environmental issue. Despite, a large number of studies in rodent and monkey models of Parkinson's disease have reported that near infrared light has neuroprotective effects on dopaminergic neurons, recent findings have shown that prolonged exposure of rodents and birds to fluorescent artificial light results in an increase of neuromelanin granules in substantia nigra and loss of dopaminergic neurons. The observed detrimental effect seems to be dependent on a direct effect of light on the substantia nigra rather than a secondary effect of the alterations of circadian rhythms. Moreover, inferences from animal models to human studies have shown a positive correlation between the prevalence of Parkinson's disease and light pollution. The present article discusses experimental evidence supporting a potentially deleterious impact of light on dopaminergic neurons and highlights the mechanisms whereby light might damage neuronal tissue. Moreover, it analyses epidemiological evidence that suggests light pollution to be an environmental risk factor for Parkinson's disease.
Address Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy. Electronic address: roberto.maggio@univaq.it
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0306-4522 ISBN Medium
Area Expedition Conference
Notes PMID:32142863 Approved no
Call Number GFZ @ kyba @ Serial 2839
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Author Chen, X.; Jia, X.; Pickering, M.
Title (up) A Nighttime Lights Adjusted Impervious Surface Index (NAISI) with Integration of Landsat Imagery and Nighttime Lights Data from International Space Station Type Journal Article
Year 2019 Publication International Journal of Applied Earth Observation and Geoinformation Abbreviated Journal International Journal of Applied Earth Observation and Geoinformation
Volume 83 Issue Pages 101889
Keywords Remote Sensing
Abstract Accurate mapping of impervious surface is essential for both urbanization monitoring and micro-ecosystem research. However, the confusion between impervious surface and bare soil is the major concern due to their high spectral similarity in optical imagery. Integration of multi-sensor images is considered to offer a better capacity for distinguishing impervious surface from background. In this paper, a new impervious surface index namely nighttime light adjusted impervious surface index (NAISI), which integrates information from Landsat and nighttime lights (NTL) data from International Space Station (NTL-ISS), is proposed. Parallel to baseline subtraction approaches, NAISI integrate the information from the first component of principal component (PC) transformation of NTL-ISS, the Soil Adjusted Vegetation Index (SAVI) and the third component of tasseled cap transform (TC3) of the Landsat data. Visual interpretation and quantitative indices (SDI, Kappa and overall accuracy) were adopted to elevate the accuracy and separability of NAISI. Comparative analysis with NTL derived light intensity, optical indices, as well as existing optical-NTL indices were conducted to examine the performance of NAISI. Results indicate that NAISI achieves a more promising capability in impervious surface mapping. This demonstrates the superiority of integration of optical and nighttime lights information for imperviousness detection.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0303-2434 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2658
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Author Rea, M.; Skinner, N.; Bullough, J.
Title (up) A Novel Barricade Warning Light System Using Wireless Communications Type Journal Article
Year 2018 Publication SAE Technical Paper 2018-01-5036 Abbreviated Journal
Volume In press Issue Pages
Keywords Lighting; Safety
Abstract Workers in construction and transportation sectors are at increased risk for work-related injuries and fatalities by nearby traffic. Barricade-mounted warning lights meeting current specifications do not always provide consistent and adequate visual guidance to drivers and can contribute to glare and reduced safety. Through an implementation of sensors and wireless communications, a novel, intelligent set of warning lights and a tablet-based interface were developed. The lights modulate between 100% and 10% of maximum intensity rather than between 100% and off in order to improve visual guidance and adjust their overall intensity based on ambient conditions. The lights can be synchronized or operated in sequential flash patterns at any frequency between 1 and 4 Hz, and sequential patterns automatically update based on global positioning satellite (GPS) locations displayed in the control interface. A successful field demonstration of the system verified that its functions were viewed favorably by transportation safety personnel.
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Notes Approved no
Call Number NC @ ehyde3 @ Serial 2117
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Author Hu, T.; Huang, X.
Title (up) A novel locally adaptive method for modeling the spatiotemporal dynamics of global electric power consumption based on DMSP-OLS nighttime stable light data Type Journal Article
Year 2019 Publication Applied Energy Abbreviated Journal Applied Energy
Volume 240 Issue Pages 778-792
Keywords Remote Sensing
Abstract Timely and reliable estimation of electricity power consumption (EPC) is essential to the rational deployment of electricity power resources. Nighttime stable light (NSL) data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) have the potential to model global 1-km gridded EPC. A processing chain to estimate EPC includes: (1) NSL data correction; and (2) regression model between EPC statistics and NSL data. For the global gridded EPC estimation, the current approach is to correct the global NSL image in a uniform manner and establish the linear relationships between NSL and EPC. However, the impacts of local socioeconomic inconsistencies on the NSL correction and model establishment are not fully considered. Therefore, in this paper, we propose a novel locally adaptive method for global EPC estimation. Firstly, we set up two options (with or without the correction) for each local area considering the global NSL image is not saturated everywhere. Secondly, three directions (forward, backward, or average) are alternatives for the inter-annual correction to remove the discontinuity effect of NSL data. Thirdly, four optional models (linear, logarithmic, exponential, or second-order polynomial) are adopted for the EPC estimation of each local area with different socioeconomic dynamic. Finally, the options for each step constitute all candidate processing chains, from which the optimal one is adaptively chosen for each local area based on the coefficient of determination. The results demonstrate that our product outperforms the existing one, at global, continental, and national scales. Particularly, the proportion of countries/districts with a high accuracy (MARE (mean of the absolute relative error)  ≤ 10%) increases from 17.8% to 57.8% and the percentage of countries/districts with inaccurate results (MARE > 50%) decreases sharply from 23.0% to 3.7%. This product can enhance the detailed understanding of the spatiotemporal dynamics of global EPC.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0306-2619 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2242
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